Overview

Dataset statistics

Number of variables46
Number of observations3061
Missing cells62709
Missing cells (%)44.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory368.0 B

Variable types

Numeric10
Categorical29
Unsupported7

Alerts

url has a high cardinality: 629 distinct values High cardinality
name has a high cardinality: 627 distinct values High cardinality
premiered has a high cardinality: 403 distinct values High cardinality
ended has a high cardinality: 106 distinct values High cardinality
officialSite has a high cardinality: 569 distinct values High cardinality
summary has a high cardinality: 553 distinct values High cardinality
webChannel.name has a high cardinality: 137 distinct values High cardinality
externals.imdb has a high cardinality: 306 distinct values High cardinality
image.medium has a high cardinality: 581 distinct values High cardinality
image.original has a high cardinality: 581 distinct values High cardinality
_links.self.href has a high cardinality: 629 distinct values High cardinality
_links.previousepisode.href has a high cardinality: 629 distinct values High cardinality
id is highly correlated with externals.thetvdbHigh correlation
runtime is highly correlated with averageRuntimeHigh correlation
averageRuntime is highly correlated with runtimeHigh correlation
updated is highly correlated with externals.tvrageHigh correlation
externals.tvrage is highly correlated with updated and 2 other fieldsHigh correlation
externals.thetvdb is highly correlated with id and 1 other fieldsHigh correlation
network.id is highly correlated with externals.tvrageHigh correlation
id is highly correlated with externals.thetvdbHigh correlation
runtime is highly correlated with averageRuntimeHigh correlation
averageRuntime is highly correlated with runtimeHigh correlation
updated is highly correlated with externals.tvrageHigh correlation
externals.tvrage is highly correlated with updated and 2 other fieldsHigh correlation
externals.thetvdb is highly correlated with id and 1 other fieldsHigh correlation
network.id is highly correlated with externals.tvrageHigh correlation
id is highly correlated with externals.thetvdbHigh correlation
runtime is highly correlated with averageRuntimeHigh correlation
averageRuntime is highly correlated with runtimeHigh correlation
externals.tvrage is highly correlated with externals.thetvdbHigh correlation
externals.thetvdb is highly correlated with id and 1 other fieldsHigh correlation
id is highly correlated with type and 22 other fieldsHigh correlation
type is highly correlated with id and 22 other fieldsHigh correlation
language is highly correlated with id and 25 other fieldsHigh correlation
status is highly correlated with type and 18 other fieldsHigh correlation
runtime is highly correlated with id and 18 other fieldsHigh correlation
averageRuntime is highly correlated with type and 19 other fieldsHigh correlation
weight is highly correlated with id and 19 other fieldsHigh correlation
updated is highly correlated with id and 19 other fieldsHigh correlation
schedule.time is highly correlated with id and 25 other fieldsHigh correlation
rating.average is highly correlated with id and 21 other fieldsHigh correlation
webChannel.id is highly correlated with language and 18 other fieldsHigh correlation
webChannel.country.name is highly correlated with id and 24 other fieldsHigh correlation
webChannel.country.code is highly correlated with id and 24 other fieldsHigh correlation
webChannel.country.timezone is highly correlated with id and 24 other fieldsHigh correlation
webChannel.officialSite is highly correlated with id and 21 other fieldsHigh correlation
externals.tvrage is highly correlated with id and 21 other fieldsHigh correlation
externals.thetvdb is highly correlated with id and 19 other fieldsHigh correlation
network.id is highly correlated with id and 24 other fieldsHigh correlation
network.name is highly correlated with id and 25 other fieldsHigh correlation
network.country.name is highly correlated with id and 25 other fieldsHigh correlation
network.country.code is highly correlated with id and 25 other fieldsHigh correlation
network.country.timezone is highly correlated with id and 25 other fieldsHigh correlation
network.officialSite is highly correlated with id and 14 other fieldsHigh correlation
_links.nextepisode.href is highly correlated with id and 20 other fieldsHigh correlation
dvdCountry.name is highly correlated with id and 18 other fieldsHigh correlation
dvdCountry.code is highly correlated with id and 18 other fieldsHigh correlation
dvdCountry.timezone is highly correlated with id and 18 other fieldsHigh correlation
language has 34 (1.1%) missing values Missing
runtime has 1007 (32.9%) missing values Missing
averageRuntime has 160 (5.2%) missing values Missing
ended has 1696 (55.4%) missing values Missing
officialSite has 398 (13.0%) missing values Missing
network has 3061 (100.0%) missing values Missing
dvdCountry has 3061 (100.0%) missing values Missing
summary has 312 (10.2%) missing values Missing
rating.average has 2634 (86.1%) missing values Missing
webChannel.id has 81 (2.6%) missing values Missing
webChannel.name has 81 (2.6%) missing values Missing
webChannel.country.name has 1592 (52.0%) missing values Missing
webChannel.country.code has 1592 (52.0%) missing values Missing
webChannel.country.timezone has 1592 (52.0%) missing values Missing
webChannel.officialSite has 1246 (40.7%) missing values Missing
externals.tvrage has 3004 (98.1%) missing values Missing
externals.thetvdb has 923 (30.2%) missing values Missing
externals.imdb has 1460 (47.7%) missing values Missing
image.medium has 155 (5.1%) missing values Missing
image.original has 155 (5.1%) missing values Missing
network.id has 2848 (93.0%) missing values Missing
network.name has 2848 (93.0%) missing values Missing
network.country.name has 2848 (93.0%) missing values Missing
network.country.code has 2848 (93.0%) missing values Missing
network.country.timezone has 2848 (93.0%) missing values Missing
network.officialSite has 3054 (99.8%) missing values Missing
_links.nextepisode.href has 2886 (94.3%) missing values Missing
webChannel has 3061 (100.0%) missing values Missing
image has 3061 (100.0%) missing values Missing
webChannel.country has 3061 (100.0%) missing values Missing
dvdCountry.name has 3034 (99.1%) missing values Missing
dvdCountry.code has 3034 (99.1%) missing values Missing
dvdCountry.timezone has 3034 (99.1%) missing values Missing
genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
network is an unsupported type, check if it needs cleaning or further analysis Unsupported
dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-08-29 15:50:14.981585
Analysis finished2022-08-29 15:50:29.851251
Duration14.87 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct629
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46836.47566
Minimum802
Maximum63761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:29.915478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile15250
Q144110
median51928
Q352799
95-th percentile59579
Maximum63761
Range62959
Interquartile range (IQR)8689

Descriptive statistics

Standard deviation12423.86229
Coefficient of variation (CV)0.2652604005
Kurtosis3.028803874
Mean46836.47566
Median Absolute Deviation (MAD)2834
Skewness-1.832174843
Sum143366452
Variance154352354.3
MonotonicityNot monotonic
2022-08-29T10:50:30.024425image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1525038
 
1.2%
5535532
 
1.0%
3060631
 
1.0%
5274330
 
1.0%
5210429
 
0.9%
5242128
 
0.9%
4791226
 
0.8%
5280626
 
0.8%
5252424
 
0.8%
5476224
 
0.8%
Other values (619)2773
90.6%
ValueCountFrequency (%)
8024
 
0.1%
15962
 
0.1%
18255
 
0.2%
22666
 
0.2%
250419
0.6%
28551
 
< 0.1%
37341
 
< 0.1%
40913
 
0.1%
50581
 
< 0.1%
60904
 
0.1%
ValueCountFrequency (%)
637613
 
0.1%
6371910
0.3%
633104
 
0.1%
631554
 
0.1%
629012
 
0.1%
627646
0.2%
625452
 
0.1%
624184
 
0.1%
623062
 
0.1%
621273
 
0.1%

url
Categorical

HIGH CARDINALITY

Distinct629
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
https://www.tvmaze.com/shows/15250/the-young-turks
 
38
https://www.tvmaze.com/shows/55355/90-day-fiance-extras
 
32
https://www.tvmaze.com/shows/30606/scishow
 
31
https://www.tvmaze.com/shows/52743/the-penalty-zone
 
30
https://www.tvmaze.com/shows/52104/twisted-fate-of-love
 
29
Other values (624)
2901 

Length

Max length85
Median length70
Mean length50.89382555
Min length38

Characters and Unicode

Total characters155786
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)4.0%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/52198/kotiki
3rd rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
4th rowhttps://www.tvmaze.com/shows/51336/core-sense
5th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/15250/the-young-turks38
 
1.2%
https://www.tvmaze.com/shows/55355/90-day-fiance-extras32
 
1.0%
https://www.tvmaze.com/shows/30606/scishow31
 
1.0%
https://www.tvmaze.com/shows/52743/the-penalty-zone30
 
1.0%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love29
 
0.9%
https://www.tvmaze.com/shows/52421/you-complete-me28
 
0.9%
https://www.tvmaze.com/shows/47912/the-wolf26
 
0.8%
https://www.tvmaze.com/shows/52806/ultimate-note26
 
0.8%
https://www.tvmaze.com/shows/52524/forever-love24
 
0.8%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze24
 
0.8%
Other values (619)2773
90.6%

Length

2022-08-29T10:50:30.173346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/15250/the-young-turks38
 
1.2%
https://www.tvmaze.com/shows/55355/90-day-fiance-extras32
 
1.0%
https://www.tvmaze.com/shows/30606/scishow31
 
1.0%
https://www.tvmaze.com/shows/52743/the-penalty-zone30
 
1.0%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love29
 
0.9%
https://www.tvmaze.com/shows/52421/you-complete-me28
 
0.9%
https://www.tvmaze.com/shows/47912/the-wolf26
 
0.8%
https://www.tvmaze.com/shows/52806/ultimate-note26
 
0.8%
https://www.tvmaze.com/shows/52524/forever-love24
 
0.8%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze24
 
0.8%
Other values (619)2773
90.6%

Most occurring characters

ValueCountFrequency (%)
/15305
 
9.8%
w12979
 
8.3%
t12409
 
8.0%
s12053
 
7.7%
o9261
 
5.9%
e8433
 
5.4%
h7709
 
4.9%
m7395
 
4.7%
a6496
 
4.2%
.6122
 
3.9%
Other values (30)57624
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter110153
70.7%
Other Punctuation24488
 
15.7%
Decimal Number15594
 
10.0%
Dash Punctuation5551
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w12979
11.8%
t12409
11.3%
s12053
10.9%
o9261
 
8.4%
e8433
 
7.7%
h7709
 
7.0%
m7395
 
6.7%
a6496
 
5.9%
c4192
 
3.8%
p3804
 
3.5%
Other values (16)25422
23.1%
Decimal Number
ValueCountFrequency (%)
52966
19.0%
21939
12.4%
41858
11.9%
11577
10.1%
01354
8.7%
61304
8.4%
31303
8.4%
91156
 
7.4%
81075
 
6.9%
71062
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/15305
62.5%
.6122
 
25.0%
:3061
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-5551
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin110153
70.7%
Common45633
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w12979
11.8%
t12409
11.3%
s12053
10.9%
o9261
 
8.4%
e8433
 
7.7%
h7709
 
7.0%
m7395
 
6.7%
a6496
 
5.9%
c4192
 
3.8%
p3804
 
3.5%
Other values (16)25422
23.1%
Common
ValueCountFrequency (%)
/15305
33.5%
.6122
 
13.4%
-5551
 
12.2%
:3061
 
6.7%
52966
 
6.5%
21939
 
4.2%
41858
 
4.1%
11577
 
3.5%
01354
 
3.0%
61304
 
2.9%
Other values (4)4596
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII155786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/15305
 
9.8%
w12979
 
8.3%
t12409
 
8.0%
s12053
 
7.7%
o9261
 
5.9%
e8433
 
5.4%
h7709
 
4.9%
m7395
 
4.7%
a6496
 
4.2%
.6122
 
3.9%
Other values (30)57624
37.0%

name
Categorical

HIGH CARDINALITY

Distinct627
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
The Young Turks
 
38
90 Day Fiancé: Extras
 
32
SciShow
 
31
The Penalty Zone
 
30
Twisted Fate of Love
 
29
Other values (622)
2901 

Length

Max length51
Median length37
Mean length16.17543287
Min length3

Characters and Unicode

Total characters49513
Distinct characters173
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)4.0%

Sample

1st rowSim for You
2nd rowКотики
3rd rowLAB с Антоном Беляевым
4th rowCore Sense
5th rowWu Shen Zhu Zai

Common Values

ValueCountFrequency (%)
The Young Turks38
 
1.2%
90 Day Fiancé: Extras32
 
1.0%
SciShow31
 
1.0%
The Penalty Zone30
 
1.0%
Twisted Fate of Love29
 
0.9%
You Complete Me28
 
0.9%
The Wolf26
 
0.8%
Ultimate Note26
 
0.8%
The Case Solver24
 
0.8%
Youths in the Breeze24
 
0.8%
Other values (617)2773
90.6%

Length

2022-08-29T10:50:30.364116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the464
 
5.4%
of190
 
2.2%
love124
 
1.4%
you79
 
0.9%
in68
 
0.8%
a61
 
0.7%
my49
 
0.6%
to47
 
0.5%
with44
 
0.5%
me44
 
0.5%
Other values (1286)7436
86.4%

Most occurring characters

ValueCountFrequency (%)
5545
 
11.2%
e4793
 
9.7%
a2754
 
5.6%
o2656
 
5.4%
i2435
 
4.9%
n2405
 
4.9%
r2400
 
4.8%
t2182
 
4.4%
s1985
 
4.0%
l1526
 
3.1%
Other values (163)20832
42.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter35035
70.8%
Uppercase Letter7787
 
15.7%
Space Separator5545
 
11.2%
Other Punctuation701
 
1.4%
Decimal Number376
 
0.8%
Dash Punctuation49
 
0.1%
Close Punctuation8
 
< 0.1%
Currency Symbol8
 
< 0.1%
Open Punctuation4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e4793
13.7%
a2754
 
7.9%
o2656
 
7.6%
i2435
 
7.0%
n2405
 
6.9%
r2400
 
6.9%
t2182
 
6.2%
s1985
 
5.7%
l1526
 
4.4%
h1311
 
3.7%
Other values (75)10588
30.2%
Uppercase Letter
ValueCountFrequency (%)
T887
 
11.4%
S664
 
8.5%
B517
 
6.6%
M476
 
6.1%
L428
 
5.5%
C416
 
5.3%
W412
 
5.3%
F377
 
4.8%
D360
 
4.6%
A345
 
4.4%
Other values (49)2905
37.3%
Other Punctuation
ValueCountFrequency (%)
:257
36.7%
'150
21.4%
.102
 
14.6%
!64
 
9.1%
,50
 
7.1%
?34
 
4.9%
&22
 
3.1%
%8
 
1.1%
#6
 
0.9%
@4
 
0.6%
Other values (2)4
 
0.6%
Decimal Number
ValueCountFrequency (%)
0133
35.4%
293
24.7%
342
 
11.2%
932
 
8.5%
132
 
8.5%
715
 
4.0%
514
 
3.7%
69
 
2.4%
84
 
1.1%
42
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
-46
93.9%
3
 
6.1%
Currency Symbol
ValueCountFrequency (%)
$4
50.0%
4
50.0%
Space Separator
ValueCountFrequency (%)
5545
100.0%
Close Punctuation
ValueCountFrequency (%)
)8
100.0%
Open Punctuation
ValueCountFrequency (%)
(4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin40051
80.9%
Common6691
 
13.5%
Cyrillic2603
 
5.3%
Greek168
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e4793
 
12.0%
a2754
 
6.9%
o2656
 
6.6%
i2435
 
6.1%
n2405
 
6.0%
r2400
 
6.0%
t2182
 
5.4%
s1985
 
5.0%
l1526
 
3.8%
h1311
 
3.3%
Other values (57)15604
39.0%
Cyrillic
ValueCountFrequency (%)
о237
 
9.1%
е197
 
7.6%
а190
 
7.3%
и176
 
6.8%
к148
 
5.7%
н145
 
5.6%
т138
 
5.3%
р129
 
5.0%
с108
 
4.1%
м70
 
2.7%
Other values (50)1065
40.9%
Common
ValueCountFrequency (%)
5545
82.9%
:257
 
3.8%
'150
 
2.2%
0133
 
2.0%
.102
 
1.5%
293
 
1.4%
!64
 
1.0%
,50
 
0.7%
-46
 
0.7%
342
 
0.6%
Other values (19)209
 
3.1%
Greek
ValueCountFrequency (%)
ς24
14.3%
έ16
 
9.5%
ε16
 
9.5%
ώ8
 
4.8%
γ8
 
4.8%
Ε8
 
4.8%
Χ8
 
4.8%
α8
 
4.8%
μ8
 
4.8%
Έ8
 
4.8%
Other values (7)56
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII46507
93.9%
Cyrillic2603
 
5.3%
None396
 
0.8%
Currency Symbols4
 
< 0.1%
Punctuation3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5545
 
11.9%
e4793
 
10.3%
a2754
 
5.9%
o2656
 
5.7%
i2435
 
5.2%
n2405
 
5.2%
r2400
 
5.2%
t2182
 
4.7%
s1985
 
4.3%
l1526
 
3.3%
Other values (69)17826
38.3%
Cyrillic
ValueCountFrequency (%)
о237
 
9.1%
е197
 
7.6%
а190
 
7.3%
и176
 
6.8%
к148
 
5.7%
н145
 
5.6%
т138
 
5.3%
р129
 
5.0%
с108
 
4.1%
м70
 
2.7%
Other values (50)1065
40.9%
None
ValueCountFrequency (%)
ø63
15.9%
é52
 
13.1%
ä26
 
6.6%
å25
 
6.3%
ς24
 
6.1%
έ16
 
4.0%
ε16
 
4.0%
ı11
 
2.8%
á10
 
2.5%
Ç8
 
2.0%
Other values (22)145
36.6%
Currency Symbols
ValueCountFrequency (%)
4
100.0%
Punctuation
ValueCountFrequency (%)
3
100.0%

type
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
Scripted
1591 
Animation
375 
Documentary
330 
Reality
262 
Talk Show
242 
Other values (6)
261 

Length

Max length11
Median length8
Mean length8.312642927
Min length4

Characters and Unicode

Total characters25445
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReality
2nd rowScripted
3rd rowDocumentary
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted1591
52.0%
Animation375
 
12.3%
Documentary330
 
10.8%
Reality262
 
8.6%
Talk Show242
 
7.9%
Sports79
 
2.6%
Variety70
 
2.3%
News56
 
1.8%
Game Show48
 
1.6%
Award Show6
 
0.2%

Length

2022-08-29T10:50:30.472158image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted1591
47.4%
animation375
 
11.2%
documentary330
 
9.8%
show298
 
8.9%
reality262
 
7.8%
talk242
 
7.2%
sports79
 
2.4%
variety70
 
2.1%
news56
 
1.7%
game48
 
1.4%
Other values (2)8
 
0.2%

Most occurring characters

ValueCountFrequency (%)
t2707
10.6%
i2673
10.5%
e2359
 
9.3%
r2076
 
8.2%
S1968
 
7.7%
c1921
 
7.5%
p1670
 
6.6%
d1597
 
6.3%
a1335
 
5.2%
n1082
 
4.3%
Other values (18)6057
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter21788
85.6%
Uppercase Letter3359
 
13.2%
Space Separator298
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t2707
12.4%
i2673
12.3%
e2359
10.8%
r2076
9.5%
c1921
8.8%
p1670
7.7%
d1597
7.3%
a1335
6.1%
n1082
 
5.0%
o1082
 
5.0%
Other values (8)3286
15.1%
Uppercase Letter
ValueCountFrequency (%)
S1968
58.6%
A381
 
11.3%
D330
 
9.8%
R262
 
7.8%
T242
 
7.2%
V70
 
2.1%
N56
 
1.7%
G48
 
1.4%
P2
 
0.1%
Space Separator
ValueCountFrequency (%)
298
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25147
98.8%
Common298
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t2707
10.8%
i2673
10.6%
e2359
9.4%
r2076
 
8.3%
S1968
 
7.8%
c1921
 
7.6%
p1670
 
6.6%
d1597
 
6.4%
a1335
 
5.3%
n1082
 
4.3%
Other values (17)5759
22.9%
Common
ValueCountFrequency (%)
298
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII25445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t2707
10.6%
i2673
10.5%
e2359
 
9.3%
r2076
 
8.2%
S1968
 
7.7%
c1921
 
7.5%
p1670
 
6.6%
d1597
 
6.3%
a1335
 
5.2%
n1082
 
4.3%
Other values (18)6057
23.8%

language
Categorical

HIGH CORRELATION
MISSING

Distinct36
Distinct (%)1.2%
Missing34
Missing (%)1.1%
Memory size24.0 KiB
English
988 
Chinese
677 
Russian
246 
Norwegian
223 
Korean
172 
Other values (31)
721 

Length

Max length10
Median length7
Mean length6.987776677
Min length4

Characters and Unicode

Total characters21152
Distinct characters43
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English988
32.3%
Chinese677
22.1%
Russian246
 
8.0%
Norwegian223
 
7.3%
Korean172
 
5.6%
Arabic66
 
2.2%
Japanese64
 
2.1%
Hindi64
 
2.1%
Spanish60
 
2.0%
Thai51
 
1.7%
Other values (26)416
13.6%

Length

2022-08-29T10:50:30.566570image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english988
32.6%
chinese677
22.4%
russian246
 
8.1%
norwegian223
 
7.4%
korean172
 
5.7%
arabic66
 
2.2%
japanese64
 
2.1%
hindi64
 
2.1%
spanish60
 
2.0%
thai51
 
1.7%
Other values (26)416
13.7%

Most occurring characters

ValueCountFrequency (%)
n2712
12.8%
i2669
12.6%
s2442
11.5%
e2130
10.1%
h1963
9.3%
g1354
 
6.4%
a1243
 
5.9%
l1088
 
5.1%
E988
 
4.7%
C677
 
3.2%
Other values (33)3886
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter18125
85.7%
Uppercase Letter3027
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n2712
15.0%
i2669
14.7%
s2442
13.5%
e2130
11.8%
h1963
10.8%
g1354
7.5%
a1243
6.9%
l1088
6.0%
r639
 
3.5%
o499
 
2.8%
Other values (13)1386
7.6%
Uppercase Letter
ValueCountFrequency (%)
E988
32.6%
C677
22.4%
R250
 
8.3%
N223
 
7.4%
K176
 
5.8%
T131
 
4.3%
S91
 
3.0%
H73
 
2.4%
P69
 
2.3%
A66
 
2.2%
Other values (10)283
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
Latin21152
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n2712
12.8%
i2669
12.6%
s2442
11.5%
e2130
10.1%
h1963
9.3%
g1354
 
6.4%
a1243
 
5.9%
l1088
 
5.1%
E988
 
4.7%
C677
 
3.2%
Other values (33)3886
18.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII21152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n2712
12.8%
i2669
12.6%
s2442
11.5%
e2130
10.1%
h1963
9.3%
g1354
 
6.4%
a1243
 
5.9%
l1088
 
5.1%
E988
 
4.7%
C677
 
3.2%
Other values (33)3886
18.4%

genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size24.0 KiB

status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
Ended
1365 
Running
1311 
To Be Determined
385 

Length

Max length16
Median length7
Mean length7.240117609
Min length5

Characters and Unicode

Total characters22162
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowTo Be Determined
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended1365
44.6%
Running1311
42.8%
To Be Determined385
 
12.6%

Length

2022-08-29T10:50:30.661956image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-29T10:50:30.750529image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ended1365
35.6%
running1311
34.2%
to385
 
10.0%
be385
 
10.0%
determined385
 
10.0%

Most occurring characters

ValueCountFrequency (%)
n5683
25.6%
d3115
14.1%
e2905
13.1%
i1696
 
7.7%
E1365
 
6.2%
R1311
 
5.9%
u1311
 
5.9%
g1311
 
5.9%
770
 
3.5%
T385
 
1.7%
Other values (6)2310
10.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17561
79.2%
Uppercase Letter3831
 
17.3%
Space Separator770
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n5683
32.4%
d3115
17.7%
e2905
16.5%
i1696
 
9.7%
u1311
 
7.5%
g1311
 
7.5%
o385
 
2.2%
t385
 
2.2%
r385
 
2.2%
m385
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
E1365
35.6%
R1311
34.2%
T385
 
10.0%
B385
 
10.0%
D385
 
10.0%
Space Separator
ValueCountFrequency (%)
770
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin21392
96.5%
Common770
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n5683
26.6%
d3115
14.6%
e2905
13.6%
i1696
 
7.9%
E1365
 
6.4%
R1311
 
6.1%
u1311
 
6.1%
g1311
 
6.1%
T385
 
1.8%
o385
 
1.8%
Other values (5)1925
 
9.0%
Common
ValueCountFrequency (%)
770
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII22162
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n5683
25.6%
d3115
14.1%
e2905
13.1%
i1696
 
7.7%
E1365
 
6.2%
R1311
 
5.9%
u1311
 
5.9%
g1311
 
5.9%
770
 
3.5%
T385
 
1.7%
Other values (6)2310
10.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct56
Distinct (%)2.7%
Missing1007
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean38.6338851
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:30.850825image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q120
median35
Q345
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)25

Descriptive statistics

Standard deviation30.78029463
Coefficient of variation (CV)0.7967175589
Kurtosis15.43237467
Mean38.6338851
Median Absolute Deviation (MAD)15
Skewness2.983404695
Sum79354
Variance947.4265376
MonotonicityNot monotonic
2022-08-29T10:50:30.957852image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45490
16.0%
30185
 
6.0%
20165
 
5.4%
60154
 
5.0%
1598
 
3.2%
12088
 
2.9%
2582
 
2.7%
5062
 
2.0%
1062
 
2.0%
1258
 
1.9%
Other values (46)610
19.9%
(Missing)1007
32.9%
ValueCountFrequency (%)
14
 
0.1%
210
 
0.3%
33
 
0.1%
418
 
0.6%
545
1.5%
67
 
0.2%
739
1.3%
829
0.9%
97
 
0.2%
1062
2.0%
ValueCountFrequency (%)
3004
 
0.1%
2403
 
0.1%
18014
 
0.5%
1304
 
0.1%
12088
2.9%
9023
 
0.8%
661
 
< 0.1%
625
 
0.2%
60154
5.0%
582
 
0.1%

averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct89
Distinct (%)3.1%
Missing160
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean36.91347811
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:31.075622image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q118
median30
Q345
95-th percentile91
Maximum300
Range299
Interquartile range (IQR)27

Descriptive statistics

Standard deviation28.12882485
Coefficient of variation (CV)0.7620204404
Kurtosis15.34896761
Mean36.91347811
Median Absolute Deviation (MAD)15
Skewness2.773331111
Sum107086
Variance791.2307872
MonotonicityNot monotonic
2022-08-29T10:50:31.238169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45465
 
15.2%
30175
 
5.7%
60135
 
4.4%
20124
 
4.1%
25116
 
3.8%
1295
 
3.1%
5086
 
2.8%
1576
 
2.5%
12070
 
2.3%
566
 
2.2%
Other values (79)1493
48.8%
(Missing)160
 
5.2%
ValueCountFrequency (%)
14
 
0.1%
215
 
0.5%
36
 
0.2%
420
 
0.7%
566
2.2%
617
 
0.6%
743
1.4%
846
1.5%
938
1.2%
1065
2.1%
ValueCountFrequency (%)
3004
0.1%
2123
0.1%
1942
0.1%
1931
 
< 0.1%
1883
0.1%
1814
0.1%
1802
0.1%
1351
 
< 0.1%
1304
0.1%
1292
0.1%

premiered
Categorical

HIGH CARDINALITY

Distinct403
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2020-12-04
 
101
2020-12-10
 
75
2020-12-14
 
65
2020-11-23
 
64
2020-11-19
 
62
Other values (398)
2694 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters30610
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)2.5%

Sample

1st row2019-03-25
2nd row2020-11-30
3rd row2019-12-17
4th row2020-10-13
5th row2020-03-08

Common Values

ValueCountFrequency (%)
2020-12-04101
 
3.3%
2020-12-1075
 
2.5%
2020-12-1465
 
2.1%
2020-11-2364
 
2.1%
2020-11-1962
 
2.0%
2020-12-1660
 
2.0%
2020-12-2158
 
1.9%
2020-12-0756
 
1.8%
2020-12-0154
 
1.8%
2020-12-1854
 
1.8%
Other values (393)2412
78.8%

Length

2022-08-29T10:50:31.382221image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-04101
 
3.3%
2020-12-1075
 
2.5%
2020-12-1465
 
2.1%
2020-11-2364
 
2.1%
2020-11-1962
 
2.0%
2020-12-1660
 
2.0%
2020-12-2158
 
1.9%
2020-12-0756
 
1.8%
2020-12-0154
 
1.8%
2020-12-1854
 
1.8%
Other values (393)2412
78.8%

Most occurring characters

ValueCountFrequency (%)
07593
24.8%
27442
24.3%
-6122
20.0%
15284
17.3%
9910
 
3.0%
3667
 
2.2%
8636
 
2.1%
4613
 
2.0%
7540
 
1.8%
6409
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number24488
80.0%
Dash Punctuation6122
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
07593
31.0%
27442
30.4%
15284
21.6%
9910
 
3.7%
3667
 
2.7%
8636
 
2.6%
4613
 
2.5%
7540
 
2.2%
6409
 
1.7%
5394
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
-6122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common30610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
07593
24.8%
27442
24.3%
-6122
20.0%
15284
17.3%
9910
 
3.0%
3667
 
2.2%
8636
 
2.1%
4613
 
2.0%
7540
 
1.8%
6409
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII30610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
07593
24.8%
27442
24.3%
-6122
20.0%
15284
17.3%
9910
 
3.0%
3667
 
2.2%
8636
 
2.1%
4613
 
2.0%
7540
 
1.8%
6409
 
1.3%

ended
Categorical

HIGH CARDINALITY
MISSING

Distinct106
Distinct (%)7.8%
Missing1696
Missing (%)55.4%
Memory size24.0 KiB
2020-12-18
 
61
2020-12-30
 
61
2020-12-11
 
59
2021-01-07
 
58
2020-12-16
 
57
Other values (101)
1069 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters13650
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)1.2%

Sample

1st row2020-12-11
2nd row2020-12-22
3rd row2020-12-08
4th row2020-12-08
5th row2020-12-01

Common Values

ValueCountFrequency (%)
2020-12-1861
 
2.0%
2020-12-3061
 
2.0%
2020-12-1159
 
1.9%
2021-01-0758
 
1.9%
2020-12-1657
 
1.9%
2021-01-0552
 
1.7%
2020-12-2249
 
1.6%
2020-12-2449
 
1.6%
2020-12-1538
 
1.2%
2020-12-2338
 
1.2%
Other values (96)843
27.5%
(Missing)1696
55.4%

Length

2022-08-29T10:50:31.515568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1861
 
4.5%
2020-12-3061
 
4.5%
2020-12-1159
 
4.3%
2021-01-0758
 
4.2%
2020-12-1657
 
4.2%
2021-01-0552
 
3.8%
2020-12-2249
 
3.6%
2020-12-2449
 
3.6%
2020-12-1538
 
2.8%
2020-12-2338
 
2.8%
Other values (96)843
61.8%

Most occurring characters

ValueCountFrequency (%)
24124
30.2%
03252
23.8%
-2730
20.0%
12397
17.6%
5200
 
1.5%
3192
 
1.4%
4183
 
1.3%
8168
 
1.2%
7161
 
1.2%
6138
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number10920
80.0%
Dash Punctuation2730
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
24124
37.8%
03252
29.8%
12397
22.0%
5200
 
1.8%
3192
 
1.8%
4183
 
1.7%
8168
 
1.5%
7161
 
1.5%
6138
 
1.3%
9105
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
-2730
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common13650
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
24124
30.2%
03252
23.8%
-2730
20.0%
12397
17.6%
5200
 
1.5%
3192
 
1.4%
4183
 
1.3%
8168
 
1.2%
7161
 
1.2%
6138
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII13650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24124
30.2%
03252
23.8%
-2730
20.0%
12397
17.6%
5200
 
1.5%
3192
 
1.4%
4183
 
1.3%
8168
 
1.2%
7161
 
1.2%
6138
 
1.0%

officialSite
Categorical

HIGH CARDINALITY
MISSING

Distinct569
Distinct (%)21.4%
Missing398
Missing (%)13.0%
Memory size24.0 KiB
https://www.tytnetwork.com
 
38
https://www.discoveryplus.co.uk/show/90-day-extras
 
32
https://www.youtube.com/user/scishow/
 
31
https://www.iqiyi.com/a_19rrhllpip.html
 
30
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=
 
29
Other values (564)
2503 

Length

Max length250
Median length89
Mean length51.15095757
Min length15

Characters and Unicode

Total characters136215
Distinct characters77
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)4.2%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttp://epic-media.ru/project/kotiki
3rd rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
4th rowhttps://www.bilibili.com/bangumi/media/md28223064
5th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html

Common Values

ValueCountFrequency (%)
https://www.tytnetwork.com38
 
1.2%
https://www.discoveryplus.co.uk/show/90-day-extras32
 
1.0%
https://www.youtube.com/user/scishow/31
 
1.0%
https://www.iqiyi.com/a_19rrhllpip.html30
 
1.0%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=29
 
0.9%
https://www.iqiyi.com/a_nvzsmw0tgx.html26
 
0.8%
https://www.iqiyi.com/lib/m_213579814.html26
 
0.8%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html24
 
0.8%
https://www.iqiyi.com/a_c4m3iuc94t.html24
 
0.8%
https://tv.nrk.no/serie/stjernestoev24
 
0.8%
Other values (559)2379
77.7%
(Missing)398
 
13.0%

Length

2022-08-29T10:50:31.619714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tytnetwork.com38
 
1.4%
https://www.discoveryplus.co.uk/show/90-day-extras32
 
1.2%
https://www.youtube.com/user/scishow31
 
1.2%
https://www.iqiyi.com/a_19rrhllpip.html30
 
1.1%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab29
 
1.1%
https://www.iqiyi.com/a_nvzsmw0tgx.html26
 
1.0%
https://www.iqiyi.com/lib/m_213579814.html26
 
1.0%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html24
 
0.9%
https://www.iqiyi.com/a_c4m3iuc94t.html24
 
0.9%
https://tv.nrk.no/serie/stjernestoev24
 
0.9%
Other values (558)2379
89.3%

Most occurring characters

ValueCountFrequency (%)
/11162
 
8.2%
t10456
 
7.7%
s6960
 
5.1%
e6832
 
5.0%
w6050
 
4.4%
o5886
 
4.3%
.5611
 
4.1%
h5086
 
3.7%
i4790
 
3.5%
p4442
 
3.3%
Other values (67)68940
50.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter89734
65.9%
Other Punctuation21623
 
15.9%
Decimal Number13758
 
10.1%
Uppercase Letter7405
 
5.4%
Dash Punctuation2389
 
1.8%
Math Symbol735
 
0.5%
Connector Punctuation571
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t10456
 
11.7%
s6960
 
7.8%
e6832
 
7.6%
w6050
 
6.7%
o5886
 
6.6%
h5086
 
5.7%
i4790
 
5.3%
p4442
 
5.0%
a4275
 
4.8%
m4048
 
4.5%
Other values (16)30909
34.4%
Uppercase Letter
ValueCountFrequency (%)
E602
 
8.1%
A574
 
7.8%
B513
 
6.9%
P460
 
6.2%
C432
 
5.8%
D365
 
4.9%
L364
 
4.9%
N309
 
4.2%
T279
 
3.8%
M268
 
3.6%
Other values (16)3239
43.7%
Other Punctuation
ValueCountFrequency (%)
/11162
51.6%
.5611
25.9%
:2919
 
13.5%
%1288
 
6.0%
?382
 
1.8%
&199
 
0.9%
!21
 
0.1%
#21
 
0.1%
,10
 
< 0.1%
'10
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
02046
14.9%
11773
12.9%
81433
10.4%
41384
10.1%
21383
10.1%
91352
9.8%
31236
9.0%
51133
8.2%
61060
7.7%
7958
7.0%
Math Symbol
ValueCountFrequency (%)
=676
92.0%
+43
 
5.9%
~16
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
-2389
100.0%
Connector Punctuation
ValueCountFrequency (%)
_571
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin97139
71.3%
Common39076
28.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t10456
 
10.8%
s6960
 
7.2%
e6832
 
7.0%
w6050
 
6.2%
o5886
 
6.1%
h5086
 
5.2%
i4790
 
4.9%
p4442
 
4.6%
a4275
 
4.4%
m4048
 
4.2%
Other values (42)38314
39.4%
Common
ValueCountFrequency (%)
/11162
28.6%
.5611
14.4%
:2919
 
7.5%
-2389
 
6.1%
02046
 
5.2%
11773
 
4.5%
81433
 
3.7%
41384
 
3.5%
21383
 
3.5%
91352
 
3.5%
Other values (15)7624
19.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII136215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/11162
 
8.2%
t10456
 
7.7%
s6960
 
5.1%
e6832
 
5.0%
w6050
 
4.4%
o5886
 
4.3%
.5611
 
4.1%
h5086
 
3.7%
i4790
 
3.5%
p4442
 
3.3%
Other values (67)68940
50.6%

weight
Real number (ℝ≥0)

HIGH CORRELATION

Distinct99
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.29010127
Minimum0
Maximum100
Zeros9
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:31.730673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q117
median29
Q348
95-th percentile92
Maximum100
Range100
Interquartile range (IQR)31

Descriptive statistics

Standard deviation26.30804439
Coefficient of variation (CV)0.7249371994
Kurtosis-0.2609319157
Mean36.29010127
Median Absolute Deviation (MAD)14
Skewness0.8418268226
Sum111084
Variance692.1131994
MonotonicityNot monotonic
2022-08-29T10:50:31.867913image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17175
 
5.7%
24171
 
5.6%
19145
 
4.7%
15125
 
4.1%
27121
 
4.0%
796
 
3.1%
393
 
3.0%
3378
 
2.5%
3571
 
2.3%
2970
 
2.3%
Other values (89)1916
62.6%
ValueCountFrequency (%)
09
 
0.3%
129
 
0.9%
243
1.4%
393
3.0%
457
1.9%
510
 
0.3%
621
 
0.7%
796
3.1%
828
 
0.9%
937
 
1.2%
ValueCountFrequency (%)
1003
 
0.1%
9922
0.7%
9819
0.6%
9721
0.7%
9611
 
0.4%
9533
1.1%
944
 
0.1%
9321
0.7%
9224
0.8%
918
 
0.3%

network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing3061
Missing (%)100.0%
Memory size24.0 KiB

dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing3061
Missing (%)100.0%
Memory size24.0 KiB

summary
Categorical

HIGH CARDINALITY
MISSING

Distinct553
Distinct (%)20.1%
Missing312
Missing (%)10.2%
Memory size24.0 KiB
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>
 
38
<p>Relive some of the memorable moments our couples have faced on their journeys so far. From whopping age gaps to complex language barriers, explore their ups and downs as they prepared to embark on their new lives together.</p>
 
32
<p><b>SciShow</b> explores the unexpected. Seven days a week, Hank Green, Michael Aranda, and Olivia Gordon delve into the scientific subjects that defy our expectations and make us even more curious!</p><p>Schedule:</p><p>Sundays — Learn about the amazing topics we can't quite make a stand-alone show about in SciShow List Show!</p><p>Mondays — Tune in for a short Dose about our weird world.</p><p>Tuesdays — Find answers to our most asked Quick Questions.</p><p>Wednesdays — Hank or Michael dives deep into a long-form Infusion episode, or an unscripted talk show or quiz show with a guest!</p><p>Thursday — Another new dose about the wonders of the world.</p><p>Fridays — Learn the latest in science News.</p><p>Saturdays — Get your quick questions answered!</p>
 
31
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>
 
30
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>
 
29
Other values (548)
2589 

Length

Max length1620
Median length595
Mean length367.2229902
Min length36

Characters and Unicode

Total characters1009496
Distinct characters177
Distinct categories15 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)3.7%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
3rd row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
4th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
5th row<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>

Common Values

ValueCountFrequency (%)
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>38
 
1.2%
<p>Relive some of the memorable moments our couples have faced on their journeys so far. From whopping age gaps to complex language barriers, explore their ups and downs as they prepared to embark on their new lives together.</p>32
 
1.0%
<p><b>SciShow</b> explores the unexpected. Seven days a week, Hank Green, Michael Aranda, and Olivia Gordon delve into the scientific subjects that defy our expectations and make us even more curious!</p><p>Schedule:</p><p>Sundays — Learn about the amazing topics we can't quite make a stand-alone show about in SciShow List Show!</p><p>Mondays — Tune in for a short Dose about our weird world.</p><p>Tuesdays — Find answers to our most asked Quick Questions.</p><p>Wednesdays — Hank or Michael dives deep into a long-form Infusion episode, or an unscripted talk show or quiz show with a guest!</p><p>Thursday — Another new dose about the wonders of the world.</p><p>Fridays — Learn the latest in science News.</p><p>Saturdays — Get your quick questions answered!</p>31
 
1.0%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>30
 
1.0%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>29
 
0.9%
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>28
 
0.9%
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>26
 
0.8%
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>26
 
0.8%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>24
 
0.8%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>24
 
0.8%
Other values (543)2461
80.4%
(Missing)312
 
10.2%

Length

2022-08-29T10:50:32.009116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the9569
 
5.7%
and6047
 
3.6%
a5069
 
3.0%
of4881
 
2.9%
to4454
 
2.6%
in3198
 
1.9%
is1921
 
1.1%
with1688
 
1.0%
his1386
 
0.8%
that1232
 
0.7%
Other values (7698)129006
76.6%

Most occurring characters

ValueCountFrequency (%)
165363
16.4%
e94951
 
9.4%
t63934
 
6.3%
a62517
 
6.2%
o58248
 
5.8%
n57966
 
5.7%
i55653
 
5.5%
s50477
 
5.0%
r48458
 
4.8%
h40191
 
4.0%
Other values (167)311738
30.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter764737
75.8%
Space Separator165761
 
16.4%
Uppercase Letter29624
 
2.9%
Other Punctuation26905
 
2.7%
Math Symbol17112
 
1.7%
Dash Punctuation2224
 
0.2%
Decimal Number2191
 
0.2%
Format268
 
< 0.1%
Open Punctuation250
 
< 0.1%
Close Punctuation250
 
< 0.1%
Other values (5)174
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e94951
12.4%
t63934
 
8.4%
a62517
 
8.2%
o58248
 
7.6%
n57966
 
7.6%
i55653
 
7.3%
s50477
 
6.6%
r48458
 
6.3%
h40191
 
5.3%
l30836
 
4.0%
Other values (67)201506
26.3%
Uppercase Letter
ValueCountFrequency (%)
T3092
 
10.4%
S2814
 
9.5%
A2142
 
7.2%
W1599
 
5.4%
C1478
 
5.0%
M1432
 
4.8%
L1417
 
4.8%
H1395
 
4.7%
Y1264
 
4.3%
I1111
 
3.8%
Other values (27)11880
40.1%
Other Letter
ValueCountFrequency (%)
6
 
6.0%
6
 
6.0%
6
 
6.0%
6
 
6.0%
6
 
6.0%
6
 
6.0%
6
 
6.0%
6
 
6.0%
4
 
4.0%
4
 
4.0%
Other values (11)44
44.0%
Other Punctuation
ValueCountFrequency (%)
,9785
36.4%
.8160
30.3%
/4470
16.6%
'2042
 
7.6%
"957
 
3.6%
!503
 
1.9%
:392
 
1.5%
?311
 
1.2%
;138
 
0.5%
&58
 
0.2%
Other values (4)89
 
0.3%
Decimal Number
ValueCountFrequency (%)
0603
27.5%
1451
20.6%
2407
18.6%
9212
 
9.7%
5111
 
5.1%
3107
 
4.9%
897
 
4.4%
479
 
3.6%
775
 
3.4%
649
 
2.2%
Math Symbol
ValueCountFrequency (%)
<8554
50.0%
>8554
50.0%
+4
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-1881
84.6%
274
 
12.3%
69
 
3.1%
Space Separator
ValueCountFrequency (%)
165363
99.8%
 398
 
0.2%
Open Punctuation
ValueCountFrequency (%)
(244
97.6%
[6
 
2.4%
Close Punctuation
ValueCountFrequency (%)
)244
97.6%
]6
 
2.4%
Currency Symbol
ValueCountFrequency (%)
$30
88.2%
4
 
11.8%
Format
ValueCountFrequency (%)
268
100.0%
Initial Punctuation
ValueCountFrequency (%)
28
100.0%
Modifier Letter
ValueCountFrequency (%)
6
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin793303
78.6%
Common215035
 
21.3%
Cyrillic1058
 
0.1%
Han76
 
< 0.1%
Katakana24
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e94951
12.0%
t63934
 
8.1%
a62517
 
7.9%
o58248
 
7.3%
n57966
 
7.3%
i55653
 
7.0%
s50477
 
6.4%
r48458
 
6.1%
h40191
 
5.1%
l30836
 
3.9%
Other values (65)230072
29.0%
Common
ValueCountFrequency (%)
165363
76.9%
,9785
 
4.6%
<8554
 
4.0%
>8554
 
4.0%
.8160
 
3.8%
/4470
 
2.1%
'2042
 
0.9%
-1881
 
0.9%
"957
 
0.4%
0603
 
0.3%
Other values (32)4666
 
2.2%
Cyrillic
ValueCountFrequency (%)
т99
 
9.4%
и97
 
9.2%
е95
 
9.0%
о95
 
9.0%
а78
 
7.4%
с66
 
6.2%
н62
 
5.9%
м56
 
5.3%
к44
 
4.2%
в39
 
3.7%
Other values (29)327
30.9%
Han
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
Other values (7)28
36.8%
Katakana
ValueCountFrequency (%)
6
25.0%
6
25.0%
6
25.0%
6
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1006983
99.8%
Cyrillic1058
 
0.1%
Punctuation687
 
0.1%
None652
 
0.1%
CJK76
 
< 0.1%
Katakana30
 
< 0.1%
Dingbats6
 
< 0.1%
Currency Symbols4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165363
16.4%
e94951
 
9.4%
t63934
 
6.3%
a62517
 
6.2%
o58248
 
5.8%
n57966
 
5.8%
i55653
 
5.5%
s50477
 
5.0%
r48458
 
4.8%
h40191
 
4.0%
Other values (75)309225
30.7%
None
ValueCountFrequency (%)
 398
61.0%
é58
 
8.9%
ä26
 
4.0%
å24
 
3.7%
ø20
 
3.1%
ö15
 
2.3%
Í12
 
1.8%
ü12
 
1.8%
ā11
 
1.7%
č10
 
1.5%
Other values (14)66
 
10.1%
Punctuation
ValueCountFrequency (%)
274
39.9%
268
39.0%
69
 
10.0%
48
 
7.0%
28
 
4.1%
Cyrillic
ValueCountFrequency (%)
т99
 
9.4%
и97
 
9.2%
е95
 
9.0%
о95
 
9.0%
а78
 
7.4%
с66
 
6.2%
н62
 
5.9%
м56
 
5.3%
к44
 
4.2%
в39
 
3.7%
Other values (29)327
30.9%
CJK
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
Other values (7)28
36.8%
Katakana
ValueCountFrequency (%)
6
20.0%
6
20.0%
6
20.0%
6
20.0%
6
20.0%
Dingbats
ValueCountFrequency (%)
6
100.0%
Currency Symbols
ValueCountFrequency (%)
4
100.0%

updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct629
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1639015196
Minimum1602172227
Maximum1661783505
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:32.119109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1602172227
5-th percentile1608999738
Q11619375021
median1645412135
Q31654593151
95-th percentile1661397711
Maximum1661783505
Range59611278
Interquartile range (IQR)35218130

Descriptive statistics

Standard deviation18591939.08
Coefficient of variation (CV)0.01134335979
Kurtosis-1.278632667
Mean1639015196
Median Absolute Deviation (MAD)12588137
Skewness-0.4753827177
Sum5.017025515 × 1012
Variance3.456601986 × 1014
MonotonicityNot monotonic
2022-08-29T10:50:32.224155image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
164819005838
 
1.2%
164011241532
 
1.0%
164476200531
 
1.0%
165497641130
 
1.0%
160953514129
 
0.9%
161963349928
 
0.9%
164821702926
 
0.8%
164917808426
 
0.8%
161247814524
 
0.8%
161846668224
 
0.8%
Other values (619)2773
90.6%
ValueCountFrequency (%)
16021722272
 
0.1%
16034670374
0.1%
16045871195
0.2%
16045871454
0.1%
16071040924
0.1%
16071675852
 
0.1%
16072788878
0.3%
16073820732
 
0.1%
16074646181
 
< 0.1%
16075487681
 
< 0.1%
ValueCountFrequency (%)
16617835054
0.1%
16617704655
0.2%
16617037572
 
0.1%
16617018305
0.2%
16616985863
 
0.1%
16616981472
 
0.1%
16616900454
0.1%
16616736374
0.1%
16616661432
 
0.1%
16616322679
0.3%

schedule.time
Categorical

HIGH CORRELATION

Distinct44
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2221 
20:00
276 
12:00
 
71
10:00
 
66
06:00
 
61
Other values (39)
366 

Length

Max length5
Median length0
Mean length1.372100621
Min length0

Characters and Unicode

Total characters4200
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.2%

Sample

1st row
2nd row10:00
3rd row23:45
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
2221
72.6%
20:00276
 
9.0%
12:0071
 
2.3%
10:0066
 
2.2%
06:0061
 
2.0%
21:0051
 
1.7%
19:0044
 
1.4%
18:0039
 
1.3%
00:0028
 
0.9%
22:0026
 
0.8%
Other values (34)178
 
5.8%

Length

2022-08-29T10:50:32.357499image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00276
32.9%
12:0071
 
8.5%
10:0066
 
7.9%
06:0061
 
7.3%
21:0051
 
6.1%
19:0044
 
5.2%
18:0039
 
4.6%
00:0028
 
3.3%
22:0026
 
3.1%
17:0022
 
2.6%
Other values (33)156
18.6%

Most occurring characters

ValueCountFrequency (%)
02071
49.3%
:840
20.0%
2535
 
12.7%
1401
 
9.5%
671
 
1.7%
861
 
1.5%
559
 
1.4%
955
 
1.3%
350
 
1.2%
735
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3360
80.0%
Other Punctuation840
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02071
61.6%
2535
 
15.9%
1401
 
11.9%
671
 
2.1%
861
 
1.8%
559
 
1.8%
955
 
1.6%
350
 
1.5%
735
 
1.0%
422
 
0.7%
Other Punctuation
ValueCountFrequency (%)
:840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02071
49.3%
:840
20.0%
2535
 
12.7%
1401
 
9.5%
671
 
1.7%
861
 
1.5%
559
 
1.4%
955
 
1.3%
350
 
1.2%
735
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII4200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02071
49.3%
:840
20.0%
2535
 
12.7%
1401
 
9.5%
671
 
1.7%
861
 
1.5%
559
 
1.4%
955
 
1.3%
350
 
1.2%
735
 
0.8%

schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size24.0 KiB

rating.average
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)7.7%
Missing2634
Missing (%)86.1%
Infinite0
Infinite (%)0.0%
Mean6.855971897
Minimum3.6
Maximum8.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:32.502526image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.6
5-th percentile5
Q16.6
median7
Q37.5
95-th percentile8.1
Maximum8.8
Range5.2
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.9395986953
Coefficient of variation (CV)0.1370482128
Kurtosis0.3286002991
Mean6.855971897
Median Absolute Deviation (MAD)0.5
Skewness-0.7552859563
Sum2927.5
Variance0.8828457081
MonotonicityNot monotonic
2022-08-29T10:50:32.650474image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
7.253
 
1.7%
6.736
 
1.2%
7.532
 
1.0%
7.723
 
0.8%
7.422
 
0.7%
721
 
0.7%
521
 
0.7%
6.821
 
0.7%
6.620
 
0.7%
7.819
 
0.6%
Other values (23)159
 
5.2%
(Missing)2634
86.1%
ValueCountFrequency (%)
3.62
 
0.1%
41
 
< 0.1%
4.31
 
< 0.1%
4.42
 
0.1%
521
0.7%
5.28
 
0.3%
5.314
0.5%
5.412
0.4%
5.64
 
0.1%
5.85
 
0.2%
ValueCountFrequency (%)
8.85
 
0.2%
8.63
 
0.1%
8.212
 
0.4%
8.113
0.4%
86
 
0.2%
7.819
0.6%
7.723
0.8%
7.64
 
0.1%
7.532
1.0%
7.422
0.7%

webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct139
Distinct (%)4.7%
Missing81
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean145.8637584
Minimum1
Maximum533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:32.760460image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median104
Q3238
95-th percentile414
Maximum533
Range532
Interquartile range (IQR)217

Descriptive statistics

Standard deviation140.2249484
Coefficient of variation (CV)0.9613419394
Kurtosis-0.4426358087
Mean145.8637584
Median Absolute Deviation (MAD)83
Skewness0.8515760513
Sum434674
Variance19663.03615
MonotonicityNot monotonic
2022-08-29T10:50:33.239339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21535
17.5%
104245
 
8.0%
1235
 
7.7%
67169
 
5.5%
118139
 
4.5%
238118
 
3.9%
17385
 
2.8%
367
 
2.2%
32960
 
2.0%
37959
 
1.9%
Other values (129)1268
41.4%
(Missing)81
 
2.6%
ValueCountFrequency (%)
1235
7.7%
224
 
0.8%
367
 
2.2%
1217
 
0.6%
1538
 
1.2%
2018
 
0.6%
21535
17.5%
224
 
0.1%
268
 
0.3%
3053
 
1.7%
ValueCountFrequency (%)
5334
 
0.1%
5291
 
< 0.1%
5189
0.3%
51617
0.6%
5109
0.3%
5075
 
0.2%
5061
 
< 0.1%
4985
 
0.2%
4933
 
0.1%
4716
 
0.2%

webChannel.name
Categorical

HIGH CARDINALITY
MISSING

Distinct137
Distinct (%)4.6%
Missing81
Missing (%)2.6%
Memory size24.0 KiB
YouTube
535 
Tencent QQ
245 
Netflix
235 
iQIYI
169 
Youku
 
139
Other values (132)
1657 

Length

Max length23
Median length19
Mean length7.718791946
Min length3

Characters and Unicode

Total characters23002
Distinct characters69
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.3%

Sample

1st rowV LIVE
2nd rowEpic Media
3rd rowКиноПоиск HD
4th rowBilibili
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
YouTube535
17.5%
Tencent QQ245
 
8.0%
Netflix235
 
7.7%
iQIYI169
 
5.5%
Youku139
 
4.5%
NRK TV118
 
3.9%
discovery+86
 
2.8%
Prime Video67
 
2.2%
HBO Max60
 
2.0%
Shahid59
 
1.9%
Other values (127)1267
41.4%
(Missing)81
 
2.6%

Length

2022-08-29T10:50:33.366846image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube551
 
13.4%
tv304
 
7.4%
qq245
 
5.9%
tencent245
 
5.9%
netflix235
 
5.7%
iqiyi169
 
4.1%
youku139
 
3.4%
nrk118
 
2.9%
discovery86
 
2.1%
hbo78
 
1.9%
Other values (164)1954
47.4%

Most occurring characters

ValueCountFrequency (%)
e2231
 
9.7%
u1600
 
7.0%
T1376
 
6.0%
o1362
 
5.9%
i1270
 
5.5%
1144
 
5.0%
t917
 
4.0%
Y867
 
3.8%
a830
 
3.6%
n760
 
3.3%
Other values (59)10645
46.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14408
62.6%
Uppercase Letter7110
30.9%
Space Separator1144
 
5.0%
Math Symbol212
 
0.9%
Decimal Number94
 
0.4%
Other Punctuation34
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2231
15.5%
u1600
11.1%
o1362
 
9.5%
i1270
 
8.8%
t917
 
6.4%
a830
 
5.8%
n760
 
5.3%
b671
 
4.7%
l659
 
4.6%
r602
 
4.2%
Other values (22)3506
24.3%
Uppercase Letter
ValueCountFrequency (%)
T1376
19.4%
Y867
12.2%
Q659
 
9.3%
V630
 
8.9%
N538
 
7.6%
I425
 
6.0%
P310
 
4.4%
B230
 
3.2%
E207
 
2.9%
R185
 
2.6%
Other values (17)1683
23.7%
Decimal Number
ValueCountFrequency (%)
252
55.3%
528
29.8%
39
 
9.6%
45
 
5.3%
Other Punctuation
ValueCountFrequency (%)
.28
82.4%
:4
 
11.8%
!2
 
5.9%
Math Symbol
ValueCountFrequency (%)
+206
97.2%
|6
 
2.8%
Space Separator
ValueCountFrequency (%)
1144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin21419
93.1%
Common1484
 
6.5%
Cyrillic99
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2231
 
10.4%
u1600
 
7.5%
T1376
 
6.4%
o1362
 
6.4%
i1270
 
5.9%
t917
 
4.3%
Y867
 
4.0%
a830
 
3.9%
n760
 
3.5%
b671
 
3.1%
Other values (42)9535
44.5%
Common
ValueCountFrequency (%)
1144
77.1%
+206
 
13.9%
252
 
3.5%
528
 
1.9%
.28
 
1.9%
39
 
0.6%
|6
 
0.4%
45
 
0.3%
:4
 
0.3%
!2
 
0.1%
Cyrillic
ValueCountFrequency (%)
и22
22.2%
о22
22.2%
к11
11.1%
с11
11.1%
П11
11.1%
н11
11.1%
К11
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII22895
99.5%
Cyrillic99
 
0.4%
None8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e2231
 
9.7%
u1600
 
7.0%
T1376
 
6.0%
o1362
 
5.9%
i1270
 
5.5%
1144
 
5.0%
t917
 
4.0%
Y867
 
3.8%
a830
 
3.6%
n760
 
3.3%
Other values (50)10538
46.0%
Cyrillic
ValueCountFrequency (%)
и22
22.2%
о22
22.2%
к11
11.1%
с11
11.1%
П11
11.1%
н11
11.1%
К11
11.1%
None
ValueCountFrequency (%)
ñ6
75.0%
é2
 
25.0%

webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct32
Distinct (%)2.2%
Missing1592
Missing (%)52.0%
Memory size24.0 KiB
China
474 
United States
194 
Norway
175 
Korea, Republic of
122 
Russian Federation
116 
Other values (27)
388 

Length

Max length25
Median length18
Mean length9.147719537
Min length5

Characters and Unicode

Total characters13438
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowKorea, Republic of
2nd rowRussian Federation
3rd rowRussian Federation
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China474
 
15.5%
United States194
 
6.3%
Norway175
 
5.7%
Korea, Republic of122
 
4.0%
Russian Federation116
 
3.8%
India64
 
2.1%
Turkey32
 
1.0%
United Kingdom29
 
0.9%
Japan26
 
0.8%
Hong Kong25
 
0.8%
Other values (22)212
 
6.9%
(Missing)1592
52.0%

Length

2022-08-29T10:50:33.519658image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china492
22.9%
united223
10.4%
states194
 
9.0%
norway175
 
8.2%
of145
 
6.8%
republic127
 
5.9%
korea122
 
5.7%
russian116
 
5.4%
federation116
 
5.4%
india64
 
3.0%
Other values (29)372
17.3%

Most occurring characters

ValueCountFrequency (%)
a1610
 
12.0%
n1299
 
9.7%
i1284
 
9.6%
e1085
 
8.1%
t766
 
5.7%
677
 
5.0%
o664
 
4.9%
r553
 
4.1%
h533
 
4.0%
C507
 
3.8%
Other values (33)4460
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter10615
79.0%
Uppercase Letter2001
 
14.9%
Space Separator677
 
5.0%
Other Punctuation145
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a1610
15.2%
n1299
12.2%
i1284
12.1%
e1085
10.2%
t766
7.2%
o664
 
6.3%
r553
 
5.2%
h533
 
5.0%
d500
 
4.7%
s478
 
4.5%
Other values (13)1843
17.4%
Uppercase Letter
ValueCountFrequency (%)
C507
25.3%
R243
12.1%
S231
11.5%
U223
11.1%
N192
 
9.6%
K189
 
9.4%
F125
 
6.2%
I74
 
3.7%
T52
 
2.6%
B38
 
1.9%
Other values (8)127
 
6.3%
Space Separator
ValueCountFrequency (%)
677
100.0%
Other Punctuation
ValueCountFrequency (%)
,145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin12616
93.9%
Common822
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a1610
12.8%
n1299
 
10.3%
i1284
 
10.2%
e1085
 
8.6%
t766
 
6.1%
o664
 
5.3%
r553
 
4.4%
h533
 
4.2%
C507
 
4.0%
d500
 
4.0%
Other values (31)3815
30.2%
Common
ValueCountFrequency (%)
677
82.4%
,145
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII13438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a1610
 
12.0%
n1299
 
9.7%
i1284
 
9.6%
e1085
 
8.1%
t766
 
5.7%
677
 
5.0%
o664
 
4.9%
r553
 
4.1%
h533
 
4.0%
C507
 
3.8%
Other values (33)4460
33.2%

webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct32
Distinct (%)2.2%
Missing1592
Missing (%)52.0%
Memory size24.0 KiB
CN
474 
US
194 
NO
175 
KR
122 
RU
116 
Other values (27)
388 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2938
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowKR
2nd rowRU
3rd rowRU
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN474
 
15.5%
US194
 
6.3%
NO175
 
5.7%
KR122
 
4.0%
RU116
 
3.8%
IN64
 
2.1%
TR32
 
1.0%
GB29
 
0.9%
JP26
 
0.8%
HK25
 
0.8%
Other values (22)212
 
6.9%
(Missing)1592
52.0%

Length

2022-08-29T10:50:33.655929image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn474
32.3%
us194
13.2%
no175
 
11.9%
kr122
 
8.3%
ru116
 
7.9%
in64
 
4.4%
tr32
 
2.2%
gb29
 
2.0%
jp26
 
1.8%
hk25
 
1.7%
Other values (22)212
14.4%

Most occurring characters

ValueCountFrequency (%)
N730
24.8%
C489
16.6%
U311
10.6%
R307
10.4%
S231
 
7.9%
O175
 
6.0%
K166
 
5.7%
I77
 
2.6%
E70
 
2.4%
B67
 
2.3%
Other values (13)315
10.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2938
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N730
24.8%
C489
16.6%
U311
10.6%
R307
10.4%
S231
 
7.9%
O175
 
6.0%
K166
 
5.7%
I77
 
2.6%
E70
 
2.4%
B67
 
2.3%
Other values (13)315
10.7%

Most occurring scripts

ValueCountFrequency (%)
Latin2938
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N730
24.8%
C489
16.6%
U311
10.6%
R307
10.4%
S231
 
7.9%
O175
 
6.0%
K166
 
5.7%
I77
 
2.6%
E70
 
2.4%
B67
 
2.3%
Other values (13)315
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2938
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N730
24.8%
C489
16.6%
U311
10.6%
R307
10.4%
S231
 
7.9%
O175
 
6.0%
K166
 
5.7%
I77
 
2.6%
E70
 
2.4%
B67
 
2.3%
Other values (13)315
10.7%

webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct32
Distinct (%)2.2%
Missing1592
Missing (%)52.0%
Memory size24.0 KiB
Asia/Shanghai
474 
America/New_York
194 
Europe/Oslo
175 
Asia/Seoul
122 
Asia/Kamchatka
116 
Other values (27)
388 

Length

Max length17
Median length16
Mean length13.09462219
Min length10

Characters and Unicode

Total characters19236
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowAsia/Seoul
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai474
 
15.5%
America/New_York194
 
6.3%
Europe/Oslo175
 
5.7%
Asia/Seoul122
 
4.0%
Asia/Kamchatka116
 
3.8%
Asia/Kolkata64
 
2.1%
Europe/Istanbul32
 
1.0%
Europe/London29
 
0.9%
Asia/Tokyo26
 
0.8%
Asia/Hong_Kong25
 
0.8%
Other values (22)212
 
6.9%
(Missing)1592
52.0%

Length

2022-08-29T10:50:33.740684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai474
32.3%
america/new_york194
13.2%
europe/oslo175
 
11.9%
asia/seoul122
 
8.3%
asia/kamchatka116
 
7.9%
asia/kolkata64
 
4.4%
europe/istanbul32
 
2.2%
europe/london29
 
2.0%
asia/tokyo26
 
1.8%
asia/hong_kong25
 
1.7%
Other values (22)212
14.4%

Most occurring characters

ValueCountFrequency (%)
a2735
14.2%
i1719
 
8.9%
/1469
 
7.6%
s1179
 
6.1%
o1175
 
6.1%
A1141
 
5.9%
h1136
 
5.9%
e1001
 
5.2%
r875
 
4.5%
n734
 
3.8%
Other values (33)6072
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14391
74.8%
Uppercase Letter3157
 
16.4%
Other Punctuation1469
 
7.6%
Connector Punctuation219
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a2735
19.0%
i1719
11.9%
s1179
8.2%
o1175
8.2%
h1136
7.9%
e1001
 
7.0%
r875
 
6.1%
n734
 
5.1%
g562
 
3.9%
u546
 
3.8%
Other values (13)2729
19.0%
Uppercase Letter
ValueCountFrequency (%)
A1141
36.1%
S613
19.4%
E353
 
11.2%
N217
 
6.9%
K212
 
6.7%
Y194
 
6.1%
O175
 
5.5%
T49
 
1.6%
H48
 
1.5%
L35
 
1.1%
Other values (8)120
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/1469
100.0%
Connector Punctuation
ValueCountFrequency (%)
_219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17548
91.2%
Common1688
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a2735
15.6%
i1719
 
9.8%
s1179
 
6.7%
o1175
 
6.7%
A1141
 
6.5%
h1136
 
6.5%
e1001
 
5.7%
r875
 
5.0%
n734
 
4.2%
S613
 
3.5%
Other values (31)5240
29.9%
Common
ValueCountFrequency (%)
/1469
87.0%
_219
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII19236
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a2735
14.2%
i1719
 
8.9%
/1469
 
7.6%
s1179
 
6.1%
o1175
 
6.1%
A1141
 
5.9%
h1136
 
5.9%
e1001
 
5.2%
r875
 
4.5%
n734
 
3.8%
Other values (33)6072
31.6%

webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct37
Distinct (%)2.0%
Missing1246
Missing (%)40.7%
Memory size24.0 KiB
https://www.youtube.com
535 
https://v.qq.com/
245 
https://www.netflix.com/
235 
https://www.iq.com/
169 
https://www.discoveryplus.com/
85 
Other values (32)
546 

Length

Max length40
Median length33
Mean length22.45730028
Min length17

Characters and Unicode

Total characters40760
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://hd.kinopoisk.ru/
3rd rowhttps://v.qq.com/
4th rowhttps://v.qq.com/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com535
17.5%
https://v.qq.com/245
 
8.0%
https://www.netflix.com/235
 
7.7%
https://www.iq.com/169
 
5.5%
https://www.discoveryplus.com/85
 
2.8%
https://www.primevideo.com67
 
2.2%
https://www.hbomax.com/60
 
2.0%
https://tv.naver.com/53
 
1.7%
https://w.mgtv.com/47
 
1.5%
https://www.paramountplus.com/30
 
1.0%
Other values (27)289
 
9.4%
(Missing)1246
40.7%

Length

2022-08-29T10:50:33.822364image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com535
29.5%
https://v.qq.com245
13.5%
https://www.netflix.com235
12.9%
https://www.iq.com169
 
9.3%
https://www.discoveryplus.com85
 
4.7%
https://www.primevideo.com67
 
3.7%
https://www.hbomax.com60
 
3.3%
https://tv.naver.com53
 
2.9%
https://w.mgtv.com47
 
2.6%
https://www.paramountplus.com30
 
1.7%
Other values (27)289
15.9%

Most occurring characters

ValueCountFrequency (%)
/4835
11.9%
t4710
11.6%
w4334
10.6%
.3619
 
8.9%
o2634
 
6.5%
p2168
 
5.3%
s2141
 
5.3%
h1949
 
4.8%
m1943
 
4.8%
c1860
 
4.6%
Other values (20)10567
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter30479
74.8%
Other Punctuation10269
 
25.2%
Dash Punctuation7
 
< 0.1%
Decimal Number5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t4710
15.5%
w4334
14.2%
o2634
8.6%
p2168
 
7.1%
s2141
 
7.0%
h1949
 
6.4%
m1943
 
6.4%
c1860
 
6.1%
u1342
 
4.4%
e1263
 
4.1%
Other values (15)6135
20.1%
Other Punctuation
ValueCountFrequency (%)
/4835
47.1%
.3619
35.2%
:1815
 
17.7%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Decimal Number
ValueCountFrequency (%)
45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin30479
74.8%
Common10281
 
25.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t4710
15.5%
w4334
14.2%
o2634
8.6%
p2168
 
7.1%
s2141
 
7.0%
h1949
 
6.4%
m1943
 
6.4%
c1860
 
6.1%
u1342
 
4.4%
e1263
 
4.1%
Other values (15)6135
20.1%
Common
ValueCountFrequency (%)
/4835
47.0%
.3619
35.2%
:1815
 
17.7%
-7
 
0.1%
45
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII40760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/4835
11.9%
t4710
11.6%
w4334
10.6%
.3619
 
8.9%
o2634
 
6.5%
p2168
 
5.3%
s2141
 
5.3%
h1949
 
4.8%
m1943
 
4.8%
c1860
 
4.6%
Other values (20)10567
25.9%

externals.tvrage
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct11
Distinct (%)19.3%
Missing3004
Missing (%)98.1%
Infinite0
Infinite (%)0.0%
Mean23860.26316
Minimum5152
Maximum47170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:33.892443image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum5152
5-th percentile5152
Q119056
median19056
Q334149
95-th percentile41967
Maximum47170
Range42018
Interquartile range (IQR)15093

Descriptive statistics

Standard deviation11571.50109
Coefficient of variation (CV)0.4849695502
Kurtosis-0.6702313355
Mean23860.26316
Median Absolute Deviation (MAD)11226
Skewness0.1352026074
Sum1360035
Variance133899637.5
MonotonicityNot monotonic
2022-08-29T10:50:33.956684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1905619
 
0.6%
341498
 
0.3%
251006
 
0.2%
51525
 
0.2%
419675
 
0.2%
302824
 
0.1%
66594
 
0.1%
471702
 
0.1%
150902
 
0.1%
382921
 
< 0.1%
(Missing)3004
98.1%
ValueCountFrequency (%)
51525
 
0.2%
66594
 
0.1%
150902
 
0.1%
1905619
0.6%
251006
 
0.2%
280081
 
< 0.1%
302824
 
0.1%
341498
0.3%
382921
 
< 0.1%
419675
 
0.2%
ValueCountFrequency (%)
471702
 
0.1%
419675
 
0.2%
382921
 
< 0.1%
341498
0.3%
302824
 
0.1%
280081
 
< 0.1%
251006
 
0.2%
1905619
0.6%
150902
 
0.1%
66594
 
0.1%

externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct434
Distinct (%)20.3%
Missing923
Missing (%)30.2%
Infinite0
Infinite (%)0.0%
Mean359124.1356
Minimum73246
Maximum419045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:34.086137image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum73246
5-th percentile265193
Q1345280
median382296
Q3392410
95-th percentile394627
Maximum419045
Range345799
Interquartile range (IQR)47130

Descriptive statistics

Standard deviation56073.36518
Coefficient of variation (CV)0.1561392277
Kurtosis9.622722396
Mean359124.1356
Median Absolute Deviation (MAD)11511
Skewness-2.810180813
Sum767807402
Variance3144222283
MonotonicityNot monotonic
2022-08-29T10:50:34.201973image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27879338
 
1.2%
26519331
 
1.0%
39221429
 
0.9%
39267928
 
0.9%
33109526
 
0.8%
39322926
 
0.8%
39338124
 
0.8%
39724724
 
0.8%
39264924
 
0.8%
36979822
 
0.7%
Other values (424)1866
61.0%
(Missing)923
30.2%
ValueCountFrequency (%)
732464
 
0.1%
767794
 
0.1%
784195
 
0.2%
788964
 
0.1%
794291
 
< 0.1%
854366
 
0.2%
10427119
0.6%
1445416
 
0.2%
1449914
 
0.1%
1454311
 
< 0.1%
ValueCountFrequency (%)
4190452
 
0.1%
4136274
0.1%
4119233
0.1%
4101876
0.2%
4100863
0.1%
4089565
0.2%
4087602
 
0.1%
4080343
0.1%
4047692
 
0.1%
4017904
0.1%

externals.imdb
Categorical

HIGH CARDINALITY
MISSING

Distinct306
Distinct (%)19.1%
Missing1460
Missing (%)47.7%
Memory size24.0 KiB
tt1714810
 
38
tt13599000
 
30
tt13568876
 
28
tt8871128
 
26
tt11492320
 
24
Other values (301)
1455 

Length

Max length10
Median length10
Mean length9.625858838
Min length9

Characters and Unicode

Total characters15411
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)3.3%

Sample

1st rowtt15127174
2nd rowtt11492320
3rd rowtt13570512
4th rowtt13570512
5th rowtt13570512

Common Values

ValueCountFrequency (%)
tt171481038
 
1.2%
tt1359900030
 
1.0%
tt1356887628
 
0.9%
tt887112826
 
0.8%
tt1149232024
 
0.8%
tt1359898824
 
0.8%
tt1245794622
 
0.7%
tt1193955020
 
0.7%
tt1353971020
 
0.7%
tt408703219
 
0.6%
Other values (296)1350
44.1%
(Missing)1460
47.7%

Length

2022-08-29T10:50:34.299365image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt171481038
 
2.4%
tt1359900030
 
1.9%
tt1356887628
 
1.7%
tt887112826
 
1.6%
tt1149232024
 
1.5%
tt1359898824
 
1.5%
tt1245794622
 
1.4%
tt1193955020
 
1.2%
tt1353971020
 
1.2%
tt408703219
 
1.2%
Other values (296)1350
84.3%

Most occurring characters

ValueCountFrequency (%)
t3202
20.8%
12043
13.3%
01427
9.3%
21277
 
8.3%
31249
 
8.1%
61210
 
7.9%
81197
 
7.8%
41027
 
6.7%
9949
 
6.2%
5927
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12209
79.2%
Lowercase Letter3202
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
12043
16.7%
01427
11.7%
21277
10.5%
31249
10.2%
61210
9.9%
81197
9.8%
41027
8.4%
9949
7.8%
5927
7.6%
7903
7.4%
Lowercase Letter
ValueCountFrequency (%)
t3202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common12209
79.2%
Latin3202
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
12043
16.7%
01427
11.7%
21277
10.5%
31249
10.2%
61210
9.9%
81197
9.8%
41027
8.4%
9949
7.8%
5927
7.6%
7903
7.4%
Latin
ValueCountFrequency (%)
t3202
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII15411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t3202
20.8%
12043
13.3%
01427
9.3%
21277
 
8.3%
31249
 
8.1%
61210
 
7.9%
81197
 
7.8%
41027
 
6.7%
9949
 
6.2%
5927
 
6.0%

image.medium
Categorical

HIGH CARDINALITY
MISSING

Distinct581
Distinct (%)20.0%
Missing155
Missing (%)5.1%
Memory size24.0 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg
 
38
https://static.tvmaze.com/uploads/images/medium_portrait/317/794301.jpg
 
32
https://static.tvmaze.com/uploads/images/medium_portrait/121/302950.jpg
 
31
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg
 
30
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg
 
29
Other values (576)
2746 

Length

Max length72
Median length71
Mean length71.02408809
Min length69

Characters and Unicode

Total characters206396
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)3.8%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg38
 
1.2%
https://static.tvmaze.com/uploads/images/medium_portrait/317/794301.jpg32
 
1.0%
https://static.tvmaze.com/uploads/images/medium_portrait/121/302950.jpg31
 
1.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg30
 
1.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg29
 
0.9%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721821.jpg28
 
0.9%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg26
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg26
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg24
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg24
 
0.8%
Other values (571)2618
85.5%
(Missing)155
 
5.1%

Length

2022-08-29T10:50:34.375288image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg38
 
1.3%
https://static.tvmaze.com/uploads/images/medium_portrait/317/794301.jpg32
 
1.1%
https://static.tvmaze.com/uploads/images/medium_portrait/121/302950.jpg31
 
1.1%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg30
 
1.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg29
 
1.0%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721821.jpg28
 
1.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg26
 
0.9%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg26
 
0.9%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg24
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg24
 
0.8%
Other values (571)2618
90.1%

Most occurring characters

ValueCountFrequency (%)
/20342
 
9.9%
t20342
 
9.9%
a14530
 
7.0%
m14530
 
7.0%
p11624
 
5.6%
s11624
 
5.6%
i11624
 
5.6%
.8718
 
4.2%
e8718
 
4.2%
o8718
 
4.2%
Other values (22)75626
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter145300
70.4%
Other Punctuation31966
 
15.5%
Decimal Number26224
 
12.7%
Connector Punctuation2906
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t20342
14.0%
a14530
10.0%
m14530
10.0%
p11624
 
8.0%
s11624
 
8.0%
i11624
 
8.0%
e8718
 
6.0%
o8718
 
6.0%
d5812
 
4.0%
u5812
 
4.0%
Other values (8)31966
22.0%
Decimal Number
ValueCountFrequency (%)
23754
14.3%
73263
12.4%
82883
11.0%
12819
10.7%
92658
10.1%
32508
9.6%
02198
8.4%
42145
8.2%
52128
8.1%
61868
7.1%
Other Punctuation
ValueCountFrequency (%)
/20342
63.6%
.8718
27.3%
:2906
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_2906
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin145300
70.4%
Common61096
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t20342
14.0%
a14530
10.0%
m14530
10.0%
p11624
 
8.0%
s11624
 
8.0%
i11624
 
8.0%
e8718
 
6.0%
o8718
 
6.0%
d5812
 
4.0%
u5812
 
4.0%
Other values (8)31966
22.0%
Common
ValueCountFrequency (%)
/20342
33.3%
.8718
14.3%
23754
 
6.1%
73263
 
5.3%
_2906
 
4.8%
:2906
 
4.8%
82883
 
4.7%
12819
 
4.6%
92658
 
4.4%
32508
 
4.1%
Other values (4)8339
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII206396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20342
 
9.9%
t20342
 
9.9%
a14530
 
7.0%
m14530
 
7.0%
p11624
 
5.6%
s11624
 
5.6%
i11624
 
5.6%
.8718
 
4.2%
e8718
 
4.2%
o8718
 
4.2%
Other values (22)75626
36.6%

image.original
Categorical

HIGH CARDINALITY
MISSING

Distinct581
Distinct (%)20.0%
Missing155
Missing (%)5.1%
Memory size24.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg
 
38
https://static.tvmaze.com/uploads/images/original_untouched/317/794301.jpg
 
32
https://static.tvmaze.com/uploads/images/original_untouched/121/302950.jpg
 
31
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg
 
30
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg
 
29
Other values (576)
2746 

Length

Max length75
Median length74
Mean length74.02408809
Min length72

Characters and Unicode

Total characters215114
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)3.8%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg38
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/317/794301.jpg32
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/121/302950.jpg31
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg30
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg29
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/721821.jpg28
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg26
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg26
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg24
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg24
 
0.8%
Other values (571)2618
85.5%
(Missing)155
 
5.1%

Length

2022-08-29T10:50:34.453083image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg38
 
1.3%
https://static.tvmaze.com/uploads/images/original_untouched/317/794301.jpg32
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/121/302950.jpg31
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg30
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg29
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721821.jpg28
 
1.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg26
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg26
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg24
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg24
 
0.8%
Other values (571)2618
90.1%

Most occurring characters

ValueCountFrequency (%)
/20342
 
9.5%
t17436
 
8.1%
a14530
 
6.8%
s11624
 
5.4%
i11624
 
5.4%
o11624
 
5.4%
p8718
 
4.1%
c8718
 
4.1%
.8718
 
4.1%
g8718
 
4.1%
Other values (23)93062
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter154018
71.6%
Other Punctuation31966
 
14.9%
Decimal Number26224
 
12.2%
Connector Punctuation2906
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t17436
 
11.3%
a14530
 
9.4%
s11624
 
7.5%
i11624
 
7.5%
o11624
 
7.5%
p8718
 
5.7%
c8718
 
5.7%
g8718
 
5.7%
m8718
 
5.7%
e8718
 
5.7%
Other values (9)43590
28.3%
Decimal Number
ValueCountFrequency (%)
23754
14.3%
73263
12.4%
82883
11.0%
12819
10.7%
92658
10.1%
32508
9.6%
02198
8.4%
42145
8.2%
52128
8.1%
61868
7.1%
Other Punctuation
ValueCountFrequency (%)
/20342
63.6%
.8718
27.3%
:2906
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_2906
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin154018
71.6%
Common61096
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t17436
 
11.3%
a14530
 
9.4%
s11624
 
7.5%
i11624
 
7.5%
o11624
 
7.5%
p8718
 
5.7%
c8718
 
5.7%
g8718
 
5.7%
m8718
 
5.7%
e8718
 
5.7%
Other values (9)43590
28.3%
Common
ValueCountFrequency (%)
/20342
33.3%
.8718
14.3%
23754
 
6.1%
73263
 
5.3%
:2906
 
4.8%
_2906
 
4.8%
82883
 
4.7%
12819
 
4.6%
92658
 
4.4%
32508
 
4.1%
Other values (4)8339
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII215114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20342
 
9.5%
t17436
 
8.1%
a14530
 
6.8%
s11624
 
5.4%
i11624
 
5.4%
o11624
 
5.4%
p8718
 
4.1%
c8718
 
4.1%
.8718
 
4.1%
g8718
 
4.1%
Other values (23)93062
43.3%

_links.self.href
Categorical

HIGH CARDINALITY

Distinct629
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
https://api.tvmaze.com/shows/15250
 
38
https://api.tvmaze.com/shows/55355
 
32
https://api.tvmaze.com/shows/30606
 
31
https://api.tvmaze.com/shows/52743
 
30
https://api.tvmaze.com/shows/52104
 
29
Other values (624)
2901 

Length

Max length34
Median length34
Mean length33.97157792
Min length32

Characters and Unicode

Total characters103987
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)4.0%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/52198
3rd rowhttps://api.tvmaze.com/shows/52933
4th rowhttps://api.tvmaze.com/shows/51336
5th rowhttps://api.tvmaze.com/shows/54033

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/1525038
 
1.2%
https://api.tvmaze.com/shows/5535532
 
1.0%
https://api.tvmaze.com/shows/3060631
 
1.0%
https://api.tvmaze.com/shows/5274330
 
1.0%
https://api.tvmaze.com/shows/5210429
 
0.9%
https://api.tvmaze.com/shows/5242128
 
0.9%
https://api.tvmaze.com/shows/4791226
 
0.8%
https://api.tvmaze.com/shows/5280626
 
0.8%
https://api.tvmaze.com/shows/5252424
 
0.8%
https://api.tvmaze.com/shows/5476224
 
0.8%
Other values (619)2773
90.6%

Length

2022-08-29T10:50:34.537834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/1525038
 
1.2%
https://api.tvmaze.com/shows/5535532
 
1.0%
https://api.tvmaze.com/shows/3060631
 
1.0%
https://api.tvmaze.com/shows/5274330
 
1.0%
https://api.tvmaze.com/shows/5210429
 
0.9%
https://api.tvmaze.com/shows/5242128
 
0.9%
https://api.tvmaze.com/shows/4791226
 
0.8%
https://api.tvmaze.com/shows/5280626
 
0.8%
https://api.tvmaze.com/shows/5252424
 
0.8%
https://api.tvmaze.com/shows/5476224
 
0.8%
Other values (619)2773
90.6%

Most occurring characters

ValueCountFrequency (%)
/12244
 
11.8%
s9183
 
8.8%
t9183
 
8.8%
h6122
 
5.9%
p6122
 
5.9%
a6122
 
5.9%
o6122
 
5.9%
.6122
 
5.9%
m6122
 
5.9%
e3061
 
2.9%
Other values (16)33584
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter67342
64.8%
Other Punctuation21427
 
20.6%
Decimal Number15218
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s9183
13.6%
t9183
13.6%
h6122
9.1%
p6122
9.1%
a6122
9.1%
o6122
9.1%
m6122
9.1%
e3061
 
4.5%
w3061
 
4.5%
c3061
 
4.5%
Other values (3)9183
13.6%
Decimal Number
ValueCountFrequency (%)
52952
19.4%
41856
12.2%
21846
12.1%
11545
10.2%
61295
8.5%
31261
8.3%
01221
8.0%
91124
 
7.4%
81071
 
7.0%
71047
 
6.9%
Other Punctuation
ValueCountFrequency (%)
/12244
57.1%
.6122
28.6%
:3061
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin67342
64.8%
Common36645
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/12244
33.4%
.6122
16.7%
:3061
 
8.4%
52952
 
8.1%
41856
 
5.1%
21846
 
5.0%
11545
 
4.2%
61295
 
3.5%
31261
 
3.4%
01221
 
3.3%
Other values (3)3242
 
8.8%
Latin
ValueCountFrequency (%)
s9183
13.6%
t9183
13.6%
h6122
9.1%
p6122
9.1%
a6122
9.1%
o6122
9.1%
m6122
9.1%
e3061
 
4.5%
w3061
 
4.5%
c3061
 
4.5%
Other values (3)9183
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII103987
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/12244
 
11.8%
s9183
 
8.8%
t9183
 
8.8%
h6122
 
5.9%
p6122
 
5.9%
a6122
 
5.9%
o6122
 
5.9%
.6122
 
5.9%
m6122
 
5.9%
e3061
 
2.9%
Other values (16)33584
32.3%

_links.previousepisode.href
Categorical

HIGH CARDINALITY

Distinct629
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
https://api.tvmaze.com/episodes/2301276
 
38
https://api.tvmaze.com/episodes/2092988
 
32
https://api.tvmaze.com/episodes/2275469
 
31
https://api.tvmaze.com/episodes/1997552
 
30
https://api.tvmaze.com/episodes/1976054
 
29
Other values (624)
2901 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters119379
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)4.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/1986873
3rd rowhttps://api.tvmaze.com/episodes/2245512
4th rowhttps://api.tvmaze.com/episodes/1964569
5th rowhttps://api.tvmaze.com/episodes/2309439

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/230127638
 
1.2%
https://api.tvmaze.com/episodes/209298832
 
1.0%
https://api.tvmaze.com/episodes/227546931
 
1.0%
https://api.tvmaze.com/episodes/199755230
 
1.0%
https://api.tvmaze.com/episodes/197605429
 
0.9%
https://api.tvmaze.com/episodes/198549628
 
0.9%
https://api.tvmaze.com/episodes/197259126
 
0.8%
https://api.tvmaze.com/episodes/200008326
 
0.8%
https://api.tvmaze.com/episodes/198807924
 
0.8%
https://api.tvmaze.com/episodes/207149424
 
0.8%
Other values (619)2773
90.6%

Length

2022-08-29T10:50:34.621469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/230127638
 
1.2%
https://api.tvmaze.com/episodes/209298832
 
1.0%
https://api.tvmaze.com/episodes/227546931
 
1.0%
https://api.tvmaze.com/episodes/199755230
 
1.0%
https://api.tvmaze.com/episodes/197605429
 
0.9%
https://api.tvmaze.com/episodes/198549628
 
0.9%
https://api.tvmaze.com/episodes/197259126
 
0.8%
https://api.tvmaze.com/episodes/200008326
 
0.8%
https://api.tvmaze.com/episodes/198807924
 
0.8%
https://api.tvmaze.com/episodes/207149424
 
0.8%
Other values (619)2773
90.6%

Most occurring characters

ValueCountFrequency (%)
/12244
 
10.3%
t9183
 
7.7%
p9183
 
7.7%
s9183
 
7.7%
e9183
 
7.7%
a6122
 
5.1%
i6122
 
5.1%
.6122
 
5.1%
m6122
 
5.1%
o6122
 
5.1%
Other values (16)39793
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter76525
64.1%
Other Punctuation21427
 
17.9%
Decimal Number21427
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t9183
12.0%
p9183
12.0%
s9183
12.0%
e9183
12.0%
a6122
8.0%
i6122
8.0%
m6122
8.0%
o6122
8.0%
h3061
 
4.0%
d3061
 
4.0%
Other values (3)9183
12.0%
Decimal Number
ValueCountFrequency (%)
23886
18.1%
92744
12.8%
12688
12.5%
32060
9.6%
71962
9.2%
01917
8.9%
81621
7.6%
51581
7.4%
61508
 
7.0%
41460
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/12244
57.1%
.6122
28.6%
:3061
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin76525
64.1%
Common42854
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/12244
28.6%
.6122
14.3%
23886
 
9.1%
:3061
 
7.1%
92744
 
6.4%
12688
 
6.3%
32060
 
4.8%
71962
 
4.6%
01917
 
4.5%
81621
 
3.8%
Other values (3)4549
 
10.6%
Latin
ValueCountFrequency (%)
t9183
12.0%
p9183
12.0%
s9183
12.0%
e9183
12.0%
a6122
8.0%
i6122
8.0%
m6122
8.0%
o6122
8.0%
h3061
 
4.0%
d3061
 
4.0%
Other values (3)9183
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII119379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/12244
 
10.3%
t9183
 
7.7%
p9183
 
7.7%
s9183
 
7.7%
e9183
 
7.7%
a6122
 
5.1%
i6122
 
5.1%
.6122
 
5.1%
m6122
 
5.1%
o6122
 
5.1%
Other values (16)39793
33.3%

network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)20.2%
Missing2848
Missing (%)93.0%
Infinite0
Infinite (%)0.0%
Mean481.4507042
Minimum8
Maximum1862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.0 KiB
2022-08-29T10:50:34.745083image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile30
Q1112
median308
Q3551
95-th percentile1808
Maximum1862
Range1854
Interquartile range (IQR)439

Descriptive statistics

Standard deviation527.8625229
Coefficient of variation (CV)1.096399939
Kurtosis1.162651283
Mean481.4507042
Median Absolute Deviation (MAD)196
Skewness1.53741927
Sum102549
Variance278638.8431
MonotonicityNot monotonic
2022-08-29T10:50:34.864871image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
11219
 
0.6%
37417
 
0.6%
180811
 
0.4%
51411
 
0.4%
3010
 
0.3%
55110
 
0.3%
1329
 
0.3%
3398
 
0.3%
3088
 
0.3%
2767
 
0.2%
Other values (33)103
 
3.4%
(Missing)2848
93.0%
ValueCountFrequency (%)
84
 
0.1%
3010
0.3%
371
 
< 0.1%
413
 
0.1%
491
 
< 0.1%
514
 
0.1%
763
 
0.1%
785
0.2%
853
 
0.1%
915
0.2%
ValueCountFrequency (%)
18623
 
0.1%
180811
0.4%
17663
 
0.1%
16832
 
0.1%
15691
 
< 0.1%
13544
 
0.1%
13204
 
0.1%
12821
 
< 0.1%
12623
 
0.1%
10754
 
0.1%

network.name
Categorical

HIGH CORRELATION
MISSING

Distinct43
Distinct (%)20.2%
Missing2848
Missing (%)93.0%
Memory size24.0 KiB
RTL4
19 
TV Globo
17 
MBC Masr
 
11
ТВ-3
 
11
USA Network
 
10
Other values (38)
145 

Length

Max length21
Median length17
Mean length7.201877934
Min length2

Characters and Unicode

Total characters1534
Distinct characters74
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)3.8%

Sample

1st rowТНТ
2nd rowCCTV-1
3rd rowТВ-3
4th rowСуббота
5th rowDMC

Common Values

ValueCountFrequency (%)
RTL419
 
0.6%
TV Globo17
 
0.6%
MBC Masr11
 
0.4%
ТВ-311
 
0.4%
USA Network10
 
0.3%
ITV Be10
 
0.3%
Tokyo MX9
 
0.3%
TV 28
 
0.3%
ТНТ8
 
0.3%
Hunan TV7
 
0.2%
Other values (33)103
 
3.4%
(Missing)2848
93.0%

Length

2022-08-29T10:50:34.967069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv50
 
14.0%
rtl419
 
5.3%
network19
 
5.3%
globo17
 
4.8%
tokyo12
 
3.4%
mbc11
 
3.1%
masr11
 
3.1%
тв-311
 
3.1%
be10
 
2.8%
itv10
 
2.8%
Other values (46)186
52.2%

Most occurring characters

ValueCountFrequency (%)
143
 
9.3%
T107
 
7.0%
o92
 
6.0%
V65
 
4.2%
e60
 
3.9%
B51
 
3.3%
r50
 
3.3%
a50
 
3.3%
S43
 
2.8%
M42
 
2.7%
Other values (64)831
54.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter660
43.0%
Lowercase Letter657
42.8%
Space Separator143
 
9.3%
Decimal Number58
 
3.8%
Dash Punctuation12
 
0.8%
Other Punctuation4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o92
14.0%
e60
 
9.1%
r50
 
7.6%
a50
 
7.6%
n40
 
6.1%
i31
 
4.7%
k31
 
4.7%
l28
 
4.3%
w27
 
4.1%
s26
 
4.0%
Other values (27)222
33.8%
Uppercase Letter
ValueCountFrequency (%)
T107
16.2%
V65
 
9.8%
B51
 
7.7%
S43
 
6.5%
M42
 
6.4%
C33
 
5.0%
Т32
 
4.8%
N29
 
4.4%
A25
 
3.8%
L24
 
3.6%
Other values (20)209
31.7%
Decimal Number
ValueCountFrequency (%)
422
37.9%
316
27.6%
111
19.0%
29
15.5%
Space Separator
ValueCountFrequency (%)
143
100.0%
Dash Punctuation
ValueCountFrequency (%)
-12
100.0%
Other Punctuation
ValueCountFrequency (%)
:4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1141
74.4%
Common217
 
14.1%
Cyrillic176
 
11.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
T107
 
9.4%
o92
 
8.1%
V65
 
5.7%
e60
 
5.3%
B51
 
4.5%
r50
 
4.4%
a50
 
4.4%
S43
 
3.8%
M42
 
3.7%
n40
 
3.5%
Other values (34)541
47.4%
Cyrillic
ValueCountFrequency (%)
Т32
18.2%
С15
 
8.5%
Н14
 
8.0%
а13
 
7.4%
и12
 
6.8%
В11
 
6.2%
й10
 
5.7%
о9
 
5.1%
Р6
 
3.4%
н6
 
3.4%
Other values (13)48
27.3%
Common
ValueCountFrequency (%)
143
65.9%
422
 
10.1%
316
 
7.4%
-12
 
5.5%
111
 
5.1%
29
 
4.1%
:4
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1358
88.5%
Cyrillic176
 
11.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
143
 
10.5%
T107
 
7.9%
o92
 
6.8%
V65
 
4.8%
e60
 
4.4%
B51
 
3.8%
r50
 
3.7%
a50
 
3.7%
S43
 
3.2%
M42
 
3.1%
Other values (41)655
48.2%
Cyrillic
ValueCountFrequency (%)
Т32
18.2%
С15
 
8.5%
Н14
 
8.0%
а13
 
7.4%
и12
 
6.8%
В11
 
6.2%
й10
 
5.7%
о9
 
5.1%
Р6
 
3.4%
н6
 
3.4%
Other values (13)48
27.3%

network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)8.5%
Missing2848
Missing (%)93.0%
Memory size24.0 KiB
United States
34 
Russian Federation
27 
Japan
24 
Netherlands
19 
United Kingdom
19 
Other values (13)
90 

Length

Max length18
Median length13
Mean length10.18309859
Min length5

Characters and Unicode

Total characters2169
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowRussian Federation
2nd rowChina
3rd rowRussian Federation
4th rowRussian Federation
5th rowEgypt

Common Values

ValueCountFrequency (%)
United States34
 
1.1%
Russian Federation27
 
0.9%
Japan24
 
0.8%
Netherlands19
 
0.6%
United Kingdom19
 
0.6%
Brazil17
 
0.6%
Egypt13
 
0.4%
Norway13
 
0.4%
Ukraine10
 
0.3%
China8
 
0.3%
Other values (8)29
 
0.9%
(Missing)2848
93.0%

Length

2022-08-29T10:50:35.058494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united53
17.0%
states34
10.9%
russian27
8.7%
federation27
8.7%
japan24
 
7.7%
netherlands19
 
6.1%
kingdom19
 
6.1%
brazil17
 
5.5%
egypt13
 
4.2%
norway13
 
4.2%
Other values (14)65
20.9%

Most occurring characters

ValueCountFrequency (%)
a236
 
10.9%
e216
 
10.0%
n199
 
9.2%
t184
 
8.5%
i180
 
8.3%
d126
 
5.8%
r110
 
5.1%
s108
 
5.0%
98
 
4.5%
o74
 
3.4%
Other values (26)638
29.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1760
81.1%
Uppercase Letter305
 
14.1%
Space Separator98
 
4.5%
Other Punctuation6
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a236
13.4%
e216
12.3%
n199
11.3%
t184
10.5%
i180
10.2%
d126
7.2%
r110
 
6.2%
s108
 
6.1%
o74
 
4.2%
l46
 
2.6%
Other values (12)281
16.0%
Uppercase Letter
ValueCountFrequency (%)
U63
20.7%
S42
13.8%
F34
11.1%
R33
10.8%
N32
10.5%
K25
 
8.2%
J24
 
7.9%
B17
 
5.6%
E13
 
4.3%
C8
 
2.6%
Other values (2)14
 
4.6%
Space Separator
ValueCountFrequency (%)
98
100.0%
Other Punctuation
ValueCountFrequency (%)
,6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2065
95.2%
Common104
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a236
11.4%
e216
 
10.5%
n199
 
9.6%
t184
 
8.9%
i180
 
8.7%
d126
 
6.1%
r110
 
5.3%
s108
 
5.2%
o74
 
3.6%
U63
 
3.1%
Other values (24)569
27.6%
Common
ValueCountFrequency (%)
98
94.2%
,6
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a236
 
10.9%
e216
 
10.0%
n199
 
9.2%
t184
 
8.5%
i180
 
8.3%
d126
 
5.8%
r110
 
5.1%
s108
 
5.0%
98
 
4.5%
o74
 
3.4%
Other values (26)638
29.4%

network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)8.5%
Missing2848
Missing (%)93.0%
Memory size24.0 KiB
US
34 
RU
27 
JP
24 
NL
19 
GB
19 
Other values (13)
90 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters426
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowRU
2nd rowCN
3rd rowRU
4th rowRU
5th rowEG

Common Values

ValueCountFrequency (%)
US34
 
1.1%
RU27
 
0.9%
JP24
 
0.8%
NL19
 
0.6%
GB19
 
0.6%
BR17
 
0.6%
EG13
 
0.4%
NO13
 
0.4%
UA10
 
0.3%
CN8
 
0.3%
Other values (8)29
 
0.9%
(Missing)2848
93.0%

Length

2022-08-29T10:50:35.157775image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
us34
16.0%
ru27
12.7%
jp24
11.3%
nl19
8.9%
gb19
8.9%
br17
8.0%
eg13
 
6.1%
no13
 
6.1%
ua10
 
4.7%
cn8
 
3.8%
Other values (8)29
13.6%

Most occurring characters

ValueCountFrequency (%)
U72
16.9%
R61
14.3%
N40
9.4%
S39
9.2%
B36
8.5%
G32
7.5%
J24
 
5.6%
P24
 
5.6%
L19
 
4.5%
A17
 
4.0%
Other values (8)62
14.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter426
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U72
16.9%
R61
14.3%
N40
9.4%
S39
9.2%
B36
8.5%
G32
7.5%
J24
 
5.6%
P24
 
5.6%
L19
 
4.5%
A17
 
4.0%
Other values (8)62
14.6%

Most occurring scripts

ValueCountFrequency (%)
Latin426
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U72
16.9%
R61
14.3%
N40
9.4%
S39
9.2%
B36
8.5%
G32
7.5%
J24
 
5.6%
P24
 
5.6%
L19
 
4.5%
A17
 
4.0%
Other values (8)62
14.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U72
16.9%
R61
14.3%
N40
9.4%
S39
9.2%
B36
8.5%
G32
7.5%
J24
 
5.6%
P24
 
5.6%
L19
 
4.5%
A17
 
4.0%
Other values (8)62
14.6%

network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)8.5%
Missing2848
Missing (%)93.0%
Memory size24.0 KiB
America/New_York
34 
Asia/Kamchatka
27 
Asia/Tokyo
24 
Europe/Amsterdam
19 
Europe/London
19 
Other values (13)
90 

Length

Max length19
Median length16
Mean length13.70422535
Min length10

Characters and Unicode

Total characters2919
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Shanghai
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAfrica/Cairo

Common Values

ValueCountFrequency (%)
America/New_York34
 
1.1%
Asia/Kamchatka27
 
0.9%
Asia/Tokyo24
 
0.8%
Europe/Amsterdam19
 
0.6%
Europe/London19
 
0.6%
America/Noronha17
 
0.6%
Africa/Cairo13
 
0.4%
Europe/Oslo13
 
0.4%
Europe/Zaporozhye10
 
0.3%
Asia/Shanghai8
 
0.3%
Other values (8)29
 
0.9%
(Missing)2848
93.0%

Length

2022-08-29T10:50:35.248293image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
america/new_york34
16.0%
asia/kamchatka27
12.7%
asia/tokyo24
11.3%
europe/amsterdam19
8.9%
europe/london19
8.9%
america/noronha17
8.0%
africa/cairo13
 
6.1%
europe/oslo13
 
6.1%
europe/zaporozhye10
 
4.7%
asia/shanghai8
 
3.8%
Other values (8)29
13.6%

Most occurring characters

ValueCountFrequency (%)
a316
 
10.8%
o290
 
9.9%
r245
 
8.4%
/213
 
7.3%
e198
 
6.8%
i170
 
5.8%
A158
 
5.4%
m118
 
4.0%
s118
 
4.0%
c96
 
3.3%
Other values (30)997
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2212
75.8%
Uppercase Letter460
 
15.8%
Other Punctuation213
 
7.3%
Connector Punctuation34
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a316
14.3%
o290
13.1%
r245
11.1%
e198
9.0%
i170
 
7.7%
m118
 
5.3%
s118
 
5.3%
c96
 
4.3%
k93
 
4.2%
u88
 
4.0%
Other values (12)480
21.7%
Uppercase Letter
ValueCountFrequency (%)
A158
34.3%
E74
16.1%
N51
 
11.1%
Y34
 
7.4%
K27
 
5.9%
T24
 
5.2%
L19
 
4.1%
S17
 
3.7%
O13
 
2.8%
C13
 
2.8%
Other values (6)30
 
6.5%
Other Punctuation
ValueCountFrequency (%)
/213
100.0%
Connector Punctuation
ValueCountFrequency (%)
_34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2672
91.5%
Common247
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a316
 
11.8%
o290
 
10.9%
r245
 
9.2%
e198
 
7.4%
i170
 
6.4%
A158
 
5.9%
m118
 
4.4%
s118
 
4.4%
c96
 
3.6%
k93
 
3.5%
Other values (28)870
32.6%
Common
ValueCountFrequency (%)
/213
86.2%
_34
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2919
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a316
 
10.8%
o290
 
9.9%
r245
 
8.4%
/213
 
7.3%
e198
 
6.8%
i170
 
5.8%
A158
 
5.4%
m118
 
4.0%
s118
 
4.0%
c96
 
3.3%
Other values (30)997
34.2%

network.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)57.1%
Missing3054
Missing (%)99.8%
Memory size24.0 KiB
https://www.hbo.com/
https://www.abc.net.au/
https://www.bbc.co.uk/bbcthree
https://www.bbc.co.uk/bbctwo

Length

Max length30
Median length20
Mean length23
Min length20

Characters and Unicode

Total characters161
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)42.9%

Sample

1st rowhttps://www.hbo.com/
2nd rowhttps://www.abc.net.au/
3rd rowhttps://www.hbo.com/
4th rowhttps://www.bbc.co.uk/bbcthree
5th rowhttps://www.hbo.com/

Common Values

ValueCountFrequency (%)
https://www.hbo.com/4
 
0.1%
https://www.abc.net.au/1
 
< 0.1%
https://www.bbc.co.uk/bbcthree1
 
< 0.1%
https://www.bbc.co.uk/bbctwo1
 
< 0.1%
(Missing)3054
99.8%

Length

2022-08-29T10:50:35.328107image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-29T10:50:35.420573image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
https://www.hbo.com4
57.1%
https://www.abc.net.au1
 
14.3%
https://www.bbc.co.uk/bbcthree1
 
14.3%
https://www.bbc.co.uk/bbctwo1
 
14.3%

Most occurring characters

ValueCountFrequency (%)
w22
13.7%
/21
13.0%
.17
10.6%
t17
10.6%
b13
8.1%
h12
7.5%
c11
6.8%
o11
6.8%
:7
 
4.3%
s7
 
4.3%
Other values (8)23
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter116
72.0%
Other Punctuation45
 
28.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w22
19.0%
t17
14.7%
b13
11.2%
h12
10.3%
c11
9.5%
o11
9.5%
s7
 
6.0%
p7
 
6.0%
m4
 
3.4%
e3
 
2.6%
Other values (5)9
7.8%
Other Punctuation
ValueCountFrequency (%)
/21
46.7%
.17
37.8%
:7
 
15.6%

Most occurring scripts

ValueCountFrequency (%)
Latin116
72.0%
Common45
 
28.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w22
19.0%
t17
14.7%
b13
11.2%
h12
10.3%
c11
9.5%
o11
9.5%
s7
 
6.0%
p7
 
6.0%
m4
 
3.4%
e3
 
2.6%
Other values (5)9
7.8%
Common
ValueCountFrequency (%)
/21
46.7%
.17
37.8%
:7
 
15.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w22
13.7%
/21
13.0%
.17
10.6%
t17
10.6%
b13
8.1%
h12
7.5%
c11
6.8%
o11
6.8%
:7
 
4.3%
s7
 
4.3%
Other values (8)23
14.3%

_links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING

Distinct38
Distinct (%)21.7%
Missing2886
Missing (%)94.3%
Memory size24.0 KiB
https://api.tvmaze.com/episodes/2379698
19 
https://api.tvmaze.com/episodes/2378189
 
10
https://api.tvmaze.com/episodes/2309440
 
9
https://api.tvmaze.com/episodes/2376727
 
9
https://api.tvmaze.com/episodes/2381295
 
9
Other values (33)
119 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6825
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)4.6%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309440
2nd rowhttps://api.tvmaze.com/episodes/2367084
3rd rowhttps://api.tvmaze.com/episodes/2371935
4th rowhttps://api.tvmaze.com/episodes/2379698
5th rowhttps://api.tvmaze.com/episodes/2374448

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/237969819
 
0.6%
https://api.tvmaze.com/episodes/237818910
 
0.3%
https://api.tvmaze.com/episodes/23094409
 
0.3%
https://api.tvmaze.com/episodes/23767279
 
0.3%
https://api.tvmaze.com/episodes/23812959
 
0.3%
https://api.tvmaze.com/episodes/23645657
 
0.2%
https://api.tvmaze.com/episodes/23784946
 
0.2%
https://api.tvmaze.com/episodes/23667176
 
0.2%
https://api.tvmaze.com/episodes/23671066
 
0.2%
https://api.tvmaze.com/episodes/23703115
 
0.2%
Other values (28)89
 
2.9%
(Missing)2886
94.3%

Length

2022-08-29T10:50:35.514014image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/237969819
 
10.9%
https://api.tvmaze.com/episodes/237818910
 
5.7%
https://api.tvmaze.com/episodes/23094409
 
5.1%
https://api.tvmaze.com/episodes/23767279
 
5.1%
https://api.tvmaze.com/episodes/23812959
 
5.1%
https://api.tvmaze.com/episodes/23645657
 
4.0%
https://api.tvmaze.com/episodes/23784946
 
3.4%
https://api.tvmaze.com/episodes/23667176
 
3.4%
https://api.tvmaze.com/episodes/23671066
 
3.4%
https://api.tvmaze.com/episodes/23744485
 
2.9%
Other values (28)89
50.9%

Most occurring characters

ValueCountFrequency (%)
/700
 
10.3%
p525
 
7.7%
s525
 
7.7%
e525
 
7.7%
t525
 
7.7%
o350
 
5.1%
a350
 
5.1%
i350
 
5.1%
.350
 
5.1%
m350
 
5.1%
Other values (16)2275
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4375
64.1%
Other Punctuation1225
 
17.9%
Decimal Number1225
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p525
12.0%
s525
12.0%
e525
12.0%
t525
12.0%
o350
8.0%
a350
8.0%
i350
8.0%
m350
8.0%
h175
 
4.0%
d175
 
4.0%
Other values (3)525
12.0%
Decimal Number
ValueCountFrequency (%)
3224
18.3%
2218
17.8%
7144
11.8%
6110
9.0%
8107
8.7%
9102
8.3%
495
7.8%
187
 
7.1%
572
 
5.9%
066
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/700
57.1%
.350
28.6%
:175
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4375
64.1%
Common2450
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/700
28.6%
.350
14.3%
3224
 
9.1%
2218
 
8.9%
:175
 
7.1%
7144
 
5.9%
6110
 
4.5%
8107
 
4.4%
9102
 
4.2%
495
 
3.9%
Other values (3)225
 
9.2%
Latin
ValueCountFrequency (%)
p525
12.0%
s525
12.0%
e525
12.0%
t525
12.0%
o350
8.0%
a350
8.0%
i350
8.0%
m350
8.0%
h175
 
4.0%
d175
 
4.0%
Other values (3)525
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/700
 
10.3%
p525
 
7.7%
s525
 
7.7%
e525
 
7.7%
t525
 
7.7%
o350
 
5.1%
a350
 
5.1%
i350
 
5.1%
.350
 
5.1%
m350
 
5.1%
Other values (16)2275
33.3%

webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing3061
Missing (%)100.0%
Memory size24.0 KiB

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing3061
Missing (%)100.0%
Memory size24.0 KiB

webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing3061
Missing (%)100.0%
Memory size24.0 KiB

dvdCountry.name
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)18.5%
Missing3034
Missing (%)99.1%
Memory size24.0 KiB
Ukraine
10 
Korea, Republic of
Japan
Russian Federation
Poland
 
1

Length

Max length18
Median length7
Mean length11.55555556
Min length5

Characters and Unicode

Total characters312
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st rowJapan
2nd rowUkraine
3rd rowKorea, Republic of
4th rowRussian Federation
5th rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine10
 
0.3%
Korea, Republic of8
 
0.3%
Japan4
 
0.1%
Russian Federation4
 
0.1%
Poland1
 
< 0.1%
(Missing)3034
99.1%

Length

2022-08-29T10:50:35.600639image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-29T10:50:35.711600image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ukraine10
21.3%
korea8
17.0%
republic8
17.0%
of8
17.0%
japan4
 
8.5%
russian4
 
8.5%
federation4
 
8.5%
poland1
 
2.1%

Most occurring characters

ValueCountFrequency (%)
a35
 
11.2%
e34
 
10.9%
i26
 
8.3%
n23
 
7.4%
r22
 
7.1%
o21
 
6.7%
20
 
6.4%
p12
 
3.8%
R12
 
3.8%
u12
 
3.8%
Other values (14)95
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter245
78.5%
Uppercase Letter39
 
12.5%
Space Separator20
 
6.4%
Other Punctuation8
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a35
14.3%
e34
13.9%
i26
10.6%
n23
9.4%
r22
9.0%
o21
8.6%
p12
 
4.9%
u12
 
4.9%
k10
 
4.1%
l9
 
3.7%
Other values (6)41
16.7%
Uppercase Letter
ValueCountFrequency (%)
R12
30.8%
U10
25.6%
K8
20.5%
J4
 
10.3%
F4
 
10.3%
P1
 
2.6%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
,8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin284
91.0%
Common28
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a35
12.3%
e34
12.0%
i26
 
9.2%
n23
 
8.1%
r22
 
7.7%
o21
 
7.4%
p12
 
4.2%
R12
 
4.2%
u12
 
4.2%
k10
 
3.5%
Other values (12)77
27.1%
Common
ValueCountFrequency (%)
20
71.4%
,8
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a35
 
11.2%
e34
 
10.9%
i26
 
8.3%
n23
 
7.4%
r22
 
7.1%
o21
 
6.7%
20
 
6.4%
p12
 
3.8%
R12
 
3.8%
u12
 
3.8%
Other values (14)95
30.4%

dvdCountry.code
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)18.5%
Missing3034
Missing (%)99.1%
Memory size24.0 KiB
UA
10 
KR
JP
RU
PL
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters54
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st rowJP
2nd rowUA
3rd rowKR
4th rowRU
5th rowUA

Common Values

ValueCountFrequency (%)
UA10
 
0.3%
KR8
 
0.3%
JP4
 
0.1%
RU4
 
0.1%
PL1
 
< 0.1%
(Missing)3034
99.1%

Length

2022-08-29T10:50:35.807960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-29T10:50:35.927679image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ua10
37.0%
kr8
29.6%
jp4
 
14.8%
ru4
 
14.8%
pl1
 
3.7%

Most occurring characters

ValueCountFrequency (%)
U14
25.9%
R12
22.2%
A10
18.5%
K8
14.8%
P5
 
9.3%
J4
 
7.4%
L1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter54
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U14
25.9%
R12
22.2%
A10
18.5%
K8
14.8%
P5
 
9.3%
J4
 
7.4%
L1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin54
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U14
25.9%
R12
22.2%
A10
18.5%
K8
14.8%
P5
 
9.3%
J4
 
7.4%
L1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U14
25.9%
R12
22.2%
A10
18.5%
K8
14.8%
P5
 
9.3%
J4
 
7.4%
L1
 
1.9%

dvdCountry.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)18.5%
Missing3034
Missing (%)99.1%
Memory size24.0 KiB
Europe/Zaporozhye
10 
Asia/Seoul
Asia/Tokyo
Asia/Kamchatka
Europe/Warsaw
 
1

Length

Max length17
Median length14
Mean length13.2962963
Min length10

Characters and Unicode

Total characters359
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st rowAsia/Tokyo
2nd rowEurope/Zaporozhye
3rd rowAsia/Seoul
4th rowAsia/Kamchatka
5th rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye10
 
0.3%
Asia/Seoul8
 
0.3%
Asia/Tokyo4
 
0.1%
Asia/Kamchatka4
 
0.1%
Europe/Warsaw1
 
< 0.1%
(Missing)3034
99.1%

Length

2022-08-29T10:50:36.023135image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-29T10:50:36.113660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye10
37.0%
asia/seoul8
29.6%
asia/tokyo4
 
14.8%
asia/kamchatka4
 
14.8%
europe/warsaw1
 
3.7%

Most occurring characters

ValueCountFrequency (%)
o47
13.1%
a40
 
11.1%
e29
 
8.1%
/27
 
7.5%
r22
 
6.1%
p21
 
5.8%
u19
 
5.3%
s17
 
4.7%
A16
 
4.5%
i16
 
4.5%
Other values (15)105
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter278
77.4%
Uppercase Letter54
 
15.0%
Other Punctuation27
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o47
16.9%
a40
14.4%
e29
10.4%
r22
7.9%
p21
7.6%
u19
6.8%
s17
 
6.1%
i16
 
5.8%
h14
 
5.0%
y14
 
5.0%
Other values (7)39
14.0%
Uppercase Letter
ValueCountFrequency (%)
A16
29.6%
E11
20.4%
Z10
18.5%
S8
14.8%
T4
 
7.4%
K4
 
7.4%
W1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin332
92.5%
Common27
 
7.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o47
14.2%
a40
12.0%
e29
 
8.7%
r22
 
6.6%
p21
 
6.3%
u19
 
5.7%
s17
 
5.1%
A16
 
4.8%
i16
 
4.8%
h14
 
4.2%
Other values (14)91
27.4%
Common
ValueCountFrequency (%)
/27
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o47
13.1%
a40
 
11.1%
e29
 
8.1%
/27
 
7.5%
r22
 
6.1%
p21
 
5.8%
u19
 
5.3%
s17
 
4.7%
A16
 
4.5%
i16
 
4.5%
Other values (15)105
29.2%

Interactions

2022-08-29T10:50:26.037670image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:17.330234image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.525559image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.497844image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.443922image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.619706image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.600825image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.449644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.349906image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.110082image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.345232image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:17.484021image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.612112image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.603936image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.532494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.742346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.682653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.533328image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.414210image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.199619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.448404image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:17.612500image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.699780image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.716842image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.658058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.839684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.754611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.643262image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.485201image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.297925image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.542896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:17.719566image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.784400image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.826828image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.750526image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.940905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.831503image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.738718image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.574742image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.401173image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.609976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:17.879193image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.878805image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.904698image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.830334image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.045051image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.930783image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.831116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.645796image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.486751image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.692711image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.031033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.064711image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.995215image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.925722image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.137519image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.037851image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.928447image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.723660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.572405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.778362image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.116687image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.163017image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.110076image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.012425image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.217399image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.118637image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.010207image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.810289image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.682393image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.883483image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.202343image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.249714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.206516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.383265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.311744image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.196518image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.103648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.881339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.796273image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:26.965244image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.308432image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.317849image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.278465image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.449373image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.419785image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.281190image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.179578image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.944607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.866431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:27.046110image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:18.447624image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:19.402534image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:20.362161image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:21.538923image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:22.514200image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:23.371703image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:24.274957image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.026366image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-08-29T10:50:25.955907image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-08-29T10:50:36.202160image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-08-29T10:50:36.408506image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-08-29T10:50:36.566185image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-08-29T10:50:36.806598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-08-29T10:50:27.333167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-08-29T10:50:28.528413image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-08-29T10:50:29.073479image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-08-29T10:50:29.647747image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnametypelanguagegenresstatusruntimeaverageRuntimepremieredendedofficialSiteweightnetworkdvdCountrysummaryupdatedschedule.timeschedule.daysrating.averagewebChannel.idwebChannel.namewebChannel.country.namewebChannel.country.codewebChannel.country.timezonewebChannel.officialSiteexternals.tvrageexternals.thetvdbexternals.imdbimage.mediumimage.original_links.self.href_links.previousepisode.hrefnetwork.idnetwork.namenetwork.country.namenetwork.country.codenetwork.country.timezonenetwork.officialSite_links.nextepisode.hrefwebChannelimagewebChannel.countrydvdCountry.namedvdCountry.codedvdCountry.timezone
041648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/12163759NaNNaN<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007[Monday, Wednesday, Friday]NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpghttps://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
152198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki15NaNNaNNone163755519110:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN510.0Epic MediaRussian FederationRUAsia/KamchatkaNoneNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpghttps://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
252933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian[Music]To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva25NaNNaN<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>165403573823:45[Saturday]NaN381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpghttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpghttps://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512308.0ТНТRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNaNNaNNaNNaN
351336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese[Action, Anime, Science-Fiction]Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306432NaNNaN<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>160458711910:00[Tuesday]NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpghttps://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
454033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html80NaNNaN<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>164942344410:00[Tuesday, Sunday]NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpghttps://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309439NaNNaNNaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2309440NaNNaNNaNNaNNaNNaN
561674https://www.tvmaze.com/shows/61674/sono-koi-mousukoshi-atatamemasukaSono koi Mousukoshi AtatamemasukaScriptedJapanese[Romance]Ended15.015.02020-10-202020-12-22https://www.paravi.jp/static/koisuko1NaNNaN<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>165091521322:00[Tuesday]NaN342.0ParaviJapanJPAsia/TokyoNoneNaN419045.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/404/1012331.jpghttps://static.tvmaze.com/uploads/images/original_untouched/404/1012331.jpghttps://api.tvmaze.com/shows/61674https://api.tvmaze.com/episodes/2315117NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
652038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None17NaNNaNNone160769796512:00[Tuesday, Wednesday, Thursday]NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpghttps://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
752038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None17NaNNaNNone160769796512:00[Tuesday, Wednesday, Thursday]NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpghttps://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
852373https://www.tvmaze.com/shows/52373/fearless-whispersFearless WhispersScriptedChinese[Drama, Romance, History]Ended60.060.02020-11-062020-12-01None17NaNNaN<p>A story revolving around a fresh graduate who holds an idealistic view of what's right and wrong, yet realizes that the very institution he chose to serve falls heavily onto a gray area caught in the struggles during chaotic times.</p>1607717005[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaNNaNNaNNaNNaNNaNNaNNaN391554.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/288/721078.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721078.jpghttps://api.tvmaze.com/shows/52373https://api.tvmaze.com/episodes/19842641282.0CCTV-1ChinaCNAsia/ShanghaiNoneNaNNaNNaNNaNNaNNaNNaN
955016https://www.tvmaze.com/shows/55016/ling-jian-zunLing Jian ZunAnimationChinese[Anime]Running10.010.02019-01-15Nonehttps://v.qq.com/x/cover/2w2legt0g8z26al.html56NaNNaN<p>The strong man was attacked and returned to his youth. He became the weakest waste young lord. He will never let go of the enemy of the previous life in this life and must make up the regret of the previous life in this life! By the time the Spirit Sword is powerful, the protagonist will be supreme in the three worlds between heaven and earth! If there is someone doesn't obey him, he will kill him with the sword!</p><p><br /> </p>1653895786[Tuesday, Friday]NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaN364730.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778535.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778535.jpghttps://api.tvmaze.com/shows/55016https://api.tvmaze.com/episodes/2336755NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

idurlnametypelanguagegenresstatusruntimeaverageRuntimepremieredendedofficialSiteweightnetworkdvdCountrysummaryupdatedschedule.timeschedule.daysrating.averagewebChannel.idwebChannel.namewebChannel.country.namewebChannel.country.codewebChannel.country.timezonewebChannel.officialSiteexternals.tvrageexternals.thetvdbexternals.imdbimage.mediumimage.original_links.self.href_links.previousepisode.hrefnetwork.idnetwork.namenetwork.country.namenetwork.country.codenetwork.country.timezonenetwork.officialSite_links.nextepisode.hrefwebChannelimagewebChannel.countrydvdCountry.namedvdCountry.codedvdCountry.timezone
305159380https://www.tvmaze.com/shows/59380/forteresses-assiegees-batailles-de-legendeForteresses assiégées, batailles de légendeDocumentaryFrench[]Running51.052.02020-12-31Nonehttps://www.zed.fr/fr/tv/distribution/catalogue/programme/forteresses-assiegees-batailles-de-legende2NaNNaN<p>Built at strategic points, and fitted with impressive fortifications and ingenious systems to counter attacks, fortresses are thought to be impenetrable. And yet, certain skillful warlords have successfully stormed them. How did they manage this?</p><p>By recounting how some of the most remarkable sieges - in ancient times or in medieval history - played out, this series revisits the construction of these megastructures and reveals the different strategies used to lay or to endure a siege. Thanks to CGI, dramatized scenes, and with the help of key experts, it immerses us in the compelling confrontation between the construction genius of the military strategists and the ingenuity of some exceptional warriors.</p>1639070620[Thursday]NaN188.0CuriosityStreamUnited StatesUSAmerica/New_YorkNoneNaNNaNNoneNaNNaNhttps://api.tvmaze.com/shows/59380https://api.tvmaze.com/episodes/2234297NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
305217046https://www.tvmaze.com/shows/17046/notruf-hafenkanteNotruf HafenkanteScriptedGerman[Drama, Crime]Running45.050.02007-01-04Nonehttps://www.zdf.de/serien/notruf-hafenkante16NaNNaNNone164535198019:25[Thursday]NaN352.0ZDFmediathekGermanyDEEurope/BusingenNoneNaN232731.0tt0940902https://static.tvmaze.com/uploads/images/medium_portrait/57/143179.jpghttps://static.tvmaze.com/uploads/images/original_untouched/57/143179.jpghttps://api.tvmaze.com/shows/17046https://api.tvmaze.com/episodes/2280401NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
30532504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/79NaNNaNNone166139771120:00[Monday, Tuesday, Wednesday, Thursday]NaNNaNNaNNaNNaNNaNNaN19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpghttps://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2331565112.0RTL4NetherlandsNLEurope/AmsterdamNonehttps://api.tvmaze.com/episodes/2379698NaNNaNNaNNaNNaNNaN
305439053https://www.tvmaze.com/shows/39053/wwe-nxt-ukWWE NXT UKSportsEnglish[]Running60.060.02018-10-17NoneNone47NaNNaN<p>The one-hour episodes will feature the biggest names from NXT UK, including Pete Dunne, Mark Andrews, Rhea Ripley, Toni Storm, Tyler Bate, Trent Seven and Wolfgang. Joining the NXT UK broadcasting team as backstage interviewer is British broadcasting personality Radzi Chinyanganya, best known for hosting ITV game show "Cannonball," and in his ongoing role as a presenter of the world's longest-running children's TV show, the BBC's "Blue Peter." Calling the action are commentators Nigel McGuinness and Vic Joseph, joined by ring announcer Andy Shepherd and NXT UK General Manager, the legendary Johnny Saint.</p>166177046515:00[Thursday]NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNaN354295.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/401/1002870.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002870.jpghttps://api.tvmaze.com/shows/39053https://api.tvmaze.com/episodes/2371312NaNNaNNaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2375913NaNNaNNaNNaNNaNNaN
305539441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish[Drama, Crime, Thriller]Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business93NaNNaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>163841189521:00[]5.0351.0BET+United StatesUSAmerica/New_YorkNoneNaNNaNtt7146326https://static.tvmaze.com/uploads/images/medium_portrait/324/810377.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/810377.jpghttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
305639441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish[Drama, Crime, Thriller]Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business93NaNNaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>163841189521:00[]5.0351.0BET+United StatesUSAmerica/New_YorkNoneNaNNaNtt7146326https://static.tvmaze.com/uploads/images/medium_portrait/324/810377.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/810377.jpghttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
305739441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish[Drama, Crime, Thriller]Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business93NaNNaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>163841189521:00[]5.0351.0BET+United StatesUSAmerica/New_YorkNoneNaNNaNtt7146326https://static.tvmaze.com/uploads/images/medium_portrait/324/810377.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/810377.jpghttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
305839441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish[Drama, Crime, Thriller]Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business93NaNNaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>163841189521:00[]5.0351.0BET+United StatesUSAmerica/New_YorkNoneNaNNaNtt7146326https://static.tvmaze.com/uploads/images/medium_portrait/324/810377.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/810377.jpghttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
305939441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish[Drama, Crime, Thriller]Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business93NaNNaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>163841189521:00[]5.0351.0BET+United StatesUSAmerica/New_YorkNoneNaNNaNtt7146326https://static.tvmaze.com/uploads/images/medium_portrait/324/810377.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/810377.jpghttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
306039441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish[Drama, Crime, Thriller]Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business93NaNNaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>163841189521:00[]5.0351.0BET+United StatesUSAmerica/New_YorkNoneNaNNaNtt7146326https://static.tvmaze.com/uploads/images/medium_portrait/324/810377.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/810377.jpghttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN